The Importance of Geochemistry in Mining Wealth

## **Chapter 2**

## Geochemistry Applied to the Exploration of Mineral Deposits

*John Luis Manrique Carreño*

## **Abstract**

Geochemistry can be applied to the exploration of mineral deposits, for which it is necessary to understand the fundamentals of geochemical prospecting, the geochemical dispersion of elements based on their chemical properties. This chapter presents the basics of geochemical prospecting including: element mobility depending on ionic potential, pH, and Eh, with examples of Cu mobility during supergenic alteration of a primary sulfide deposit, a brief overview of sampling/geochemical prospecting methods, as well as a case study of the geochemical prospecting study carried out in the vanadium (V), uranium (U), and zinc (Zn) sedimentary mineral deposit of Puyango, Ecuador, in which anomalous and subanomalous values were detected in rock samples of various pathfinder elements of V and U.

**Keywords:** geochemical prospecting, mineral deposits, ionic potential, mobility, redox

## **1. Introduction**

Geochemical prospecting is the earth science that applies the theoretical knowledge of geochemistry with the aim of being able to locate mineral deposits, through the study of the primary and secondary dispersion of the elements, performing studies of lithogeochemistry, stream sediments, surface water, soil, and other methods [1, 2].

This chapter shows a review of the basic concepts of geochemical prospecting, taking as an example the mobility of copper (Cu) in during supergenic alteration of a primary sulfide deposit, depending on the ionic potential (charge/radius ratio of the ion), the hydrogen potential (pH), and the redox potential (Eh) [1, 2]. It also includes a brief description of methods (soils, lithogeochemistry, stream sediments, hydrogeochemistry), as well as the case study of geochemical prospecting carried out, in a sedimentary mineral deposit, in Puyango, Ecuador. In this study, anomalous and subanomalous values of several pathfinder elements of vanadium (V) and uranium (U) mineral deposits were detected, among which the following stand out: phosphorus (P2O5 >5.12 wt.%), nickel (Ni >1824 ppm) and, yttrium (Y >219 ppm), among the most important and subanomalies of barium (Ba >1459 ppm) and lead (Pb >32 ppm).

## **2. Mineral deposits**

Mineral deposit is a mineralization (referring to an area of the crust where ores were deposited) of sufficient size and grade (concentration), which under favorable circumstances could be exploited with economic benefits, which has sufficient reserves [3].

The concentration of the metals in the deposits varies widely in a range of few parts per million (1–100 g/t or ppm) in noble metals such as platinum (Pt), palladium (Pd), gold (Au), silver (Ag), at a low percentage (1–10 wt.%) for Cu, zinc (Zn), lead (Pb), and higher grade or tenor (40–60 wt.%) for aluminum (Al), chromium (Cr), iron (Fe), and aggregates.

Mineral deposits can be classified from the genetic point of view into five main types: 1) deposits of magmatic segregation ((chromites, iron-titanium-vanadium (Fe-Ti-V), nickel-copper (Ni-Cu) sulfides, platinum group elements (PGEs), diamonds, carbonatites)), 2) pegmatite deposits (( tin-niobium-tantalum (Sn-Nb-Ta), uranium-thorium (U-Th), lithium (Li), rare earth elements (REE)), 3) hydrothermal deposits (volcanogenic massive sulfurs Cu-Zn-Pb, SEDEX Ag-Pb-Zn, Mississippi Valley type (MVT) Ag-Pb-Zn, epithermal Au-Ag, copper-molybdenum-gold (Cu-Mo-Au) porphyry, 4) metamorphic deposits (polymetallic Skarn, graphite), 5) sedimentary deposits ((placers, laterites, Banded Iron Formations (BIFs), Li brines, U in sandstones, among others)) [3, 4].

## **3. Geochemical prospecting fundaments**

It is mainly concerned with studying the enrichment or impoverishment of certain chemical elements in the vicinity of mineral deposits [5]. Geochemical prospecting is done by systematic measurements of one or more chemical parameters, usually at trace concentrations, of naturally occurring materials in the Earth's crust. The types of samples that are collected include rocks, soils, gossan, river or lake sediments, groundwater, surface water, steam or gases, and vegetation [5] (**Figure 1**).

Primary geochemical dispersion mainly affects the migration of elements of economic interest due to processes, such as the formation and crystallization of magmas and hydrothermal activity. At the local level, these processes can lead to an enrichment or impoverishment of the elements, generating geochemical anomalies [1, 5].

Halos are enriched or depleted in various elements as a result of introduction or redistribution related to mineralization formation phenomena. The shape and size of the halo are exceptionally variable due to the various mobility characteristics of the elements in solution and microstructures in the rocks [1, 2].

The redistribution of chemical elements on or near the Earth's surface due to weathering, transport, sedimentation, and/or biological activity is classified as secondary geochemical dispersion. The secondary geochemical dispersion halo comprises the dispersed remnants of mineralization, caused by surface processes of chemical and physical weathering and the redistribution of the primary patterns. The halo can be recognized in samples taken from soil, rocks, sediments, vegetation, groundwater, and volatiles, at a distance of meters to tens of kilometers [2].

"Pathfinder" or "indicator or tracer" elements (**Table 1**) are characteristic parameters in geochemical prospecting. These are relatively mobile elements due to the physical-chemical conditions of the solutions in which they are found [1].

*Geochemistry Applied to the Exploration of Mineral Deposits DOI: http://dx.doi.org/10.5772/intechopen.103941*

#### **Figure 1.**

*Types of samples collected: rock, soil, and surface water (source: author).*


#### **Table 1.**

*Examples of pathfinders in some types of mineral deposits.*

The ionic potential is the charge/radius ionic ratio, which together with the pH and Eh allows us to understand the mobility of chemical elements during geochemical dispersion, being important parameters for geochemical prospecting [1, 2]. Ions with

ionic potential less than 3 can be soluble in water, for example: alkaline cations (Li+ , Na+ , K+ ), alkaline earth cations (Ca2+, Mg2+), transition metal cations (Fe2+, Cu2+, Cd2+, Zn2+, Pb2+). Ions with an ionic potential between 3 and 12 will be insoluble under certain pH conditions, examples: Fe3+, Al3+, Si4+, Zr4+, Pb4+, REE3+, Th4+, Nb5+. Ions with ionic potential greater than 12 will form soluble cations or anions, examples: P5+ (phosphate), As5+, S6+ (sulfate), Se6+, U6+ (uranyl), Mo6+.

An example of secondary geochemical dispersion can occur due to Cu sulfide weathering and erosion, in which surface waters percolate to primary sulfide deposits, oxidizing many ores and producing solvents that dissolve other minerals. The chemical reaction observed below describes the oxidation process of chalcopyrite (Cu ore) in waters rich in oxygen and carbon dioxide, producing goethite (gossan), Cu2+ (in solution), sulfate, sulfuric acid, and carbonic acid [3, 5]:

$$\mathrm{CuFeS}\_2 + \mathrm{O}\_2 + \mathrm{H}\_2\mathrm{O} + \mathrm{CO}\_2\mathrm{-} \mathrm{Fe(OH)}\_3 + \mathrm{Cu}^{2+} + \mathrm{SO}\_4{}^{2-} + \mathrm{H}\_2\mathrm{SO}\_4 + \mathrm{H}\_2\mathrm{CO}\_3 \tag{1}$$

Cu2+ in oxidizing environments and with acidic pH (<4) is a soluble cation; therefore, it can be leached from the mineral deposit in surface waters and underground waters. If the pH is higher, various secondary minerals can be formed such as: chalcanthite (CuSO4), azurite (Cu3(CO3)2(OH)2), malachite (Cu2(CO3)(OH)2), including tenorite (CuO) at alkaline pH. This process is known as supergenic sulfide alteration and may be useful in geochemical prospecting for Cu sulfide mineral deposits [3, 4].

## **3.1 Geochemical anomalies**

The purpose of geochemical prospecting studies is to find geochemical anomalies, which are abnormal chemical patterns in a region. For this, the background values, threshold, subanomalies, and anomalies must be established, which are statistically calculated from the data. The "background" values are characterized by the normal range of concentration of elements in regional perspective rather than localized mineral occurrences. It is significant to establish the background value of the area against anomalies due to the accumulation of economic minerals, if any, they can be identified [1, 5].

The arithmetic mean (average) is obviously skewed by some high scattered values. The most frequent value (median) tends to be within the relatively narrow range and is considered to represent the normal or background abundance for that particular element in that area.

The "threshold" (Eq. (2)) value is defined as the probable upper limit or lower limit of the background value, at some statistically precise confidence level. Any sample that exceeds this threshold is considered possibly abnormal and belongs to a separate population. The following equation is usually used to calculate it:

$$\text{Threshold} = \text{Background} \,(\text{median}) + \text{standard deviation} \tag{2}$$

The subanomaly is calculated using the background + twice the standard deviation, while the anomalies are calculated with the background plus three times the standard deviation.

## **4. Geochemical prospecting methods**

In general terms, they can be classified into the following types depending on the sampling stages, the nature of the terrain, the signal associated with the

mineralization, the type of analytical instrumentation available, and finally, the time and cost allowable for the program [5]:

Pedogeochemistry (soil sampling). Lithogeochemistry (rock sampling). Sampling of fluvial sediments. Sampling of heavy minerals. Hydrogeochemical sampling. Geochemistry of radiogenic isotopes. Geochemical sampling of glacial sediments. Vegetation sampling. Gas sampling.

Some of the afore mentioned methods are described below:

### **4.1 Soil sampling**

Soil is the unconsolidated product of weathering. It is usually found at or near its source of formation such as residual soils. It can be transported over long distances, forming alluvial soils. It is widely used in geochemical prospecting and often produces successful results.

Anomalous element enrichment from underlying mineralization may occur due to secondary dispersion in overlying soil, weathered product, and groundwater during weathering and leaching processes. The dispersion of the elements can be large, forming an exploration target larger than the actual size of the deposit.

#### **4.2 Lithogeochemistry**

Rock sampling is useful during regional work to recognize favorable geochemical provinces and favorable host rocks to host mineral deposits. Most of the epigenetic and syngenetic mineral deposits show primary dispersion around the mineralization, due to the presence of abnormally high values of the trace elements.

Lithogeochemistry aims to identify primary dispersion, diagnosis of other geochemical characteristics, and association of trace elements, which are different in sterile rocks.

Rock outcrop can be sampled directly by breaking up a small hand sample using a geological hammer or hammer and chisel. Generally, 1–3 kg is a suitable sample size (mass). Sampling is based on the analysis of fresh rocks or individual minerals. Sampling is conducted on a uniform grid across a geologic terrain that includes various rock types from fresh outcrops, wall rocks, and core samples.

#### **4.3 Sampling of fluvial sediments**

River sediment sampling is the most widely used in all reconnaissance and detailed study of watersheds. Many minerals, particularly sulfide minerals, are unstable in the weathering environment, breaking down as a result of oxidation and other chemical reactions. The process will produce secondary dispersion of both minerals and trace elements. Elements will move in solid form and in solution greater relative distances within the basin drainage.

The mobility of different elements will vary significantly, between fine-grained particles and, eventually, in detrital rock fragments, clay minerals, organic and inorganic colloids enriched in ore minerals, and in pathfinders, which are deposited downstream.

The optimum size fraction varies in different environments, and generally 80 mesh size is recommended. Samples are generally collected in natural sediment traps along streams.

#### **4.4 Hydrogeochemical sampling**

There are two types of water sources, i.e., groundwater and surface water; they have very different chemical and physical properties. Groundwater is produced in springs and wells. It has a better potential in geochemical prospecting especially if it is acidic (low pH) by dissolving and transporting metallic elements such as Cu, Pb, Zn, Mo, Sn, S, U, Ni, and Co more than in surface waters, due to chemical weathering and oxidation followed by leaching.

Surface water from streams, rivers, and oceans has less dissolving power, and finegrained sediments absorb much of the metals carried by the water. River water samples and sediment samples are collected simultaneously for analysis.

Water samples are easy to obtain. About a liter of water is collected and stored in a special container. Metal solubility decreases with increasing pH 4–7. Therefore, the pH is recorded at the time of sampling and other physicochemical parameters (Eh, temperature, salinity, total dissolved solids, among others). Suspended solids are filtered before analysis.

## **5. Case of study: U, V, Zn sedimentary mineral deposit of Puyango, Ecuador**

Here, the outcome of a preliminary study on the geochemical prospecting of a set of rock samples of the Puyango sedimentary deposit in Ecuador is presented, focusing on the quantification of certain trace elements in whole rock samples. Analytical techniques such as X-ray fluorescence and inductively coupled plasma mass spectrometry were used. The chemical obtained data were used to determinate and quantify the concentrations for the majority and some particularly economic trace chemical elements such as U, V, and Zn.

#### **5.1 Geology of Puyango sedimentary deposit**

The study area is a part of the Alamor—Lancones basin [6] and is located between the Amotape Tahuín Block of Paleozoic age to the west and the Celica continental volcanic arc to the east [7]. This Late Cretaceous basin is of marine origin, composed of a turbiditic sequence, whose siliciclastic sediments were supplied from the west, and the vulcanoclastic sediments were supplied from the east [8]. The Chirimoyo and Guineo micro-watersheds are geologically located in the Early Cretaceous Ciano, Zapotillo, and Cazaderos (**Figure 2**) sedimentary formations initially identified as belonging to the Alamor group [9], but later detailed studies in the Cazaderos Formation have differentiated the sequences from various sedimentary environments, identified informally, such as Bosque de Piedra and Puyango Formations [8]. At present, they are identified according to the outcropping site as Quebrada Los Zábalos Unit

## *Geochemistry Applied to the Exploration of Mineral Deposits DOI: http://dx.doi.org/10.5772/intechopen.103941*

**Figure 2.** *Geological map of Puyango sector (source: author).*

and Puyango Unit (**Figure 2**), maintaining the Zapotillo and Ciano Formations identified in the first instance [10].

Rocks of Paleozoic age initially identified as Metamorphic Series Tahuín by Kennerley (1973) [9], now defined as Amotape—Tahuín Block, within which the Tahuín Semipelitic Division [11] comprises the informal units, El Tigre and La Victoria. The El Tigre unit is exposed to the north of the study area characterized by sedimentary rocks and low-grade metamorphic sequences, with immature mediumgrain sandstones (La Victoria unit) interbedded with fissile shales of brown color and meta-sandstone from fine-grained.

The Early Cretaceous sedimentary rocks are formed by the Quebrada los Zábalos unit that lies to the north, overlying discordant contact with the El Tigre unit. It is constituted by basal layers of silicified fine-grained sandstones, thick conglomerates with subangular clasts of metamorphic composition and volcanic, coarse volcanic sandstones, very compact fine sandstones containing incrusted fossil trunks, and volcanoclastic middle sandstones containing outcrop fossil trunks [10]. The Puyango Unit occupies a strip of E-W direction. The rocks of this unit are chemical sediments made of black limestones and bituminous limestones interspersed with calcareous sandstones. The Puyango Unit (**Figure 2**) through paleontological interpretations is attributed to early to late Albian age [12, 13]. It is considered that the Puyango unit is of a platform environment below the wave train allowing the deposition of calcium carbonate in an anoxic environment, the sandstones are interpreted as distal turbidites. The Unit is found discordantly to the Quebrada Los Zábalos Unit. The unit is strongly deformed, and the erosion of the Pre-Campanian makes it difficult to determine its thickness (approximately 300 m) [10].

Late Cretaceous rocks are attributed to the Ciano Units made up of fine-grained sandstones, limonites, and shales. The Zapotillo Unit that overlies the Ciano Unit is made up of black shales and grawacas, flysh type. The Cazaderos Unit is found out discordantly to the calcareous rocks of the Puyango unit to the north and south to the rocks of the Ciano and Zapotillo units, while in the eastern part, they discordantly cover the metamorphic rocks of the El Tigre unit. The unit consists of brown, medium-grained sandstones, black shales interspersed with siltstones, and is attributed to an environment of turbiditic forearc sequences due to its fossiliferous content [8], indicating this faunal association of a late Campanian to Maastrichtian age.

### **5.2 Method**

Rock samples were collected in outcrops, approximately 1 kg of fresh material per sample, 30 samples in were taken in Puyango sector, Ecuador, some rock replicas were taken for internal verification. The samples were dried at 105 <sup>o</sup> C for 24 hours in the oven, then they were cut, crushed, and pulverized. The chemical analyses were made in Actlabs, Canada, carried out using the analytical package: Code 4LITHO, Major Elements Fusion ICP(WRA)/Trace Elements Fusion ICP/MS(WRA4B2), detecting the following elements (with its detection limits or lower limits): Si (0.01 wt.%), Al (0.01 wt.%), Fe (0.01 wt.%), Mn (0.01 wt.%), Mg (0.01 wt.%), Ca (0.01 wt.%), Na (0.01 wt.%), K (0.01 wt.%), Ti (0.01 wt.%), P (0.01 wt.%), Zr (2 ppm), Sr (2 ppm), Cr (20 ppm), Ba (2 ppm), Y (1 ppm), Rb (2 ppm), Ni (20 ppm), Zn (30 ppm), Pb (5 ppm), V (5 ppm), U (1 ppm), and Th (1 ppm). XRF was used for internal verification of samples, using the USGS reference material code SGR-1b (Green River Shale), in the Laboratory of Analytical Geochemistry of the Department of Geosciences of the Universidad Técnica Particular de Loja, Ecuador.

#### **5.3 Results**

The statistical parameters were calculated: minimum, maximum, mean, median, and standard deviation (**Table 2**), according to which black bituminous limestones have the mean U content of 27 ppm, reaching the maximum value of 266 ppm (**Figure 3b**), while the mean content of Ni is 331 ppm, reaching the maximum value of 2937 ppm. As for V and Zn, the mean values are 1897 ppm V and 1048 ppm Zn, with maximum values of 6837 and 4704 ppm, respectively (**Figure 3a**). The content of another element of economic interest, yttrium (Y), widely ranges, reaching the maximum value of 257 ppm (**Figure 3b**).

To calculate the background value, the median of the values was used, for the threshold the median + standard deviation was used, for the values of subanomalies the median + twice the standard deviation was used and, finally, to calculate the anomalies, the median + three times the standard deviation (**Table 3**).

#### **5.4 Final considerations**

The calculations in the dataset in rock samples of Puyango sector, Ecuador, identify anomalies of U (>158 ppm), V (>6440 ppm), Zn (>3959 ppm), P2O5 (>5.12 wt.%), Ni (>1824 ppm), and Y (>219 ppm), among the most important and subanomalies of Ba (>1459 ppm) and Pb (>32 ppm). All of these elements are pathfinders for U in sedimentary mineral deposits.


*Geochemistry Applied to the Exploration of Mineral Deposits DOI: http://dx.doi.org/10.5772/intechopen.103941*

*\* Min: minimum; Max: maximum; Mean; Median; Standard Deviation in wt.% (SiO2 to LOI) and in ppm (trace elements).*

*\*\*% Loss on ignition at 1000o C.*

#### **Table 2.**

*Statistical parameters of the chemical composition of the Puyango deposit rocks.*


#### *Geochemistry and Mineral Resources*


#### **Table 3.**

*Geochemical anomalies in the data set.*

**Figure 3.**

*(a) Box plot of trace elements contents (Ni, Zn, and V); and (b) Box plot of trace elements contents (Y and U) in Puyango deposit.*

## **6. Conclusions**

Geochemical prospecting is an important tool in the early stages of exploration of mineral deposits, since it allows delimiting anomalous areas that could be favorable for the discovery of a mineral deposit of economic interest.

To carry out a geochemical prospecting study, it is necessary to know the geochemical fundamentals that control the mobility of the different elements: ionic potential (charge/radius ratio of the ions, physicochemical parameters such as Eh and pH, among others).

When a mineral deposit is formed, some elements (pathfinders) will be dispersed to a greater extent, which can be used as tracers of the deposit.

Data from a case study of geochemical prospecting of the sedimentary mineral deposit of V, U, and Zn from Puyango, Ecuador, in which anomalous and

subanomalous values of several pathfinder elements associated with elements of economic interest were detected, among which stand out: P2O5 (>5.12 wt.%), Ni (>1824 ppm), and Y (>219 ppm), among the most important and subanomalies of Ba (>1459 ppm) and Pb (>32 ppm).

## **Acknowledgements**

I thank the department of Geosciences and the Research Vice-rectorate of the Universidad Técnica Particular de Loja, Ecuador, for their support in this research.

## **Author details**

John Luis Manrique Carreño Universidad Técnica Particular de Loja, Dep., Geociencias, Loja, Ecuador

\*Address all correspondence to: jlmanrique@utpl.edu.ec

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## **References**

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[3] Pohl WL. Economic Geology Principles and Practice. Metals, Minerals, Coal and Hydrocarbons— Introduction to Formation and Sustainable Exploitation of Mineral Deposits. West Sussex, UK: Wiley— Blackwell; 2011. p. 699

[4] Neukirchen F, Ries G. The World of Mineral Deposits. Switzerland: Springer; 2020. p. 378. DOI: org/10.1007/978-3- 030-34346-0

[5] Haldar SK. Mineral Exploration. Principles and Applications. Oxford, UK: Elsevier; 2013. p. 333

[6] Eguez A, Poma O. The Alamor-Lancones Basin in the Geodynamic Context of the Andes of Huancabamba, SW Ecuador. In: Fourth Conferences in Earth Sciences, National Polytechnic School. Ecuador: Quito; 2001. (In Spanish)

[7] Jaillard H, Bengtson P, Bulot L, Dhont A, Laubacher G, Robert E. Stratigraphy of the western Celica basin (SW Ecuador). In: Third ISAG. France: St. Malo; 1996. p. 17

[8] Jaillard H, Laubache G, Bengtson P, Dhondt A, Bulot L. Stratigraphy and evolution of the cretaceous fore arc celica-lancones basin of southwestern Ecuador. Journal of South American Earth Sciences. 1999;**12**:51-68

[9] Kenerley J. Geology of the Loja Province, Southern Ecuador. London Institute of Geological Sciences; 1973 Report 23

[10] National Institute of Geological Metallurgical Mining Research (INIGEMM). Technical Report, Puyango Geological Sheet. Scale. 2013;**1**:50000. (In Spanish)

[11] Aspden J, Bonilla W, Duque P. The el Oro Metamorphic complex, Ecuador: Geology and Economic Mineral Deposits. Overseas Geology and Mineral Resources. Vol. 67. Keyworth, Nottingham: British Geological Survey; 1995

[12] Bristow C, Hoffstetter R. International Stratigraphic Lexicon. Vol. 51977. Fascicle 5. Ecuador

[13] Shoemaker R. The Geology and Paleontology of the Cretaceous Sediments of the Puyango River Valley, Provinces of Loja and El Oro, Ecuador. Ecuadorian Subcommittee PREDESUR —Towson State University— PREDESUR. Quito, Ecuador; 1982. Publication No. 64 (in Spanish)

## **Chapter 3**

## Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition, Source Rock, and Tectonic Background

*Segun A. Akinyemi, Olajide F. Adebayo, Henry Y. Madukwe, Adeyinka O. Aturamu and Olusola A. OlaOlorun*

## **Abstract**

Study of lithofacies identification, geochemical characterization of shales is vital to the provenance, paleoweathering, and tectonic setting reconstruction. The combination of morphological analysis, bulk chemical analysis and in-situ multielement analysis was used to investigate the provenance, source area weathering, and depositional setting of outcropped Maastrichtian shale sequence of the Mamu Formation, Anambra Basin in Nigeria. Ten representative shale samples were examined by scanning electron microscopy/energy dispersive spectroscopy (SEM/EDS). Geochemical analysis was performed by X-ray fluorescence (XRF) Spectroscopy and Laser Ablation-Induced Coupled Plasma Mass Spectrometry (LA-ICPMS) techniques. The structural and morphological development of kaolinite in the outcropped shale samples of Mamu Formation is due to mechanical disintegration during transportation and re-deposition. Major oxides such as SiO2, Al2O3 and Fe2O3 constitute greater than 86% of the bulk composition. The weathering indices suggest highly weathered source materials. The plot of Cr versus Ni indicated the studied samples are Late Archean shale. Binary plots of trace elements suggest derivation from acidic or felsic sources rather than intermediate or basic source rocks. Ternary plot of Na2O + K2O, SiO2/10 and CaO + MgO indicated multiple sources such as felsic igneous rocks or recycled residues of quartz-rich. Tectonic discrimination diagram depict a typical Passive Margin field.

**Keywords:** mineralogy, geochemistry, provenance, tectonic-setting, depositional history, formation

## **1. Introduction**

The Mamu Formation (Middle-Upper Maastrichtian) in the Anambra Basin is categorized by fossiliferous dark gray, indurated, and fissile shale. In addition, it is typically overlain by the intercalation of sand and shale facies sequence with coal inter-beds previously deposited under surface marine settings [1]. Selected studies have examined the Mamu Formation, Anambra Basin based on the following; stratigraphic/biostratigraphy [2–5], sedimentology and depositional environments [6], sequence stratigraphy [7, 8], palynology [1, 9–11], coal characterization [12–14], petroleum potential [15–17], palynofacies and kerogen analysis [18], geochemical indicator [19–21] and ichnology and lithofacies [22].

Some authors have indicated that analysis of the major elemental geochemistry of sedimentary rocks is useful in discerning its tectonic background [23, 24]. However, trace elements such as; La, Y, Sc, Cr, Th, Zr, Hf and Nb, mostly combined with TiO2 are suitable for determining the provenance and tectonic settings. This is attributed to the comparatively poor mobility throughout sedimentary deposition and short habitation periods in seawater [25, 26]. The study by Armstrong-Altrin et al. [25] reported that all sedimentary rocks principally derived from Precambrian terrains could be predisposed to variations from the source materials. The comparative distribution of immovable elements showed diverse concentrations in felsic and basic rocks. For example, the immobile elements La and Th (enriched in felsic rocks) and Sc, Cr, and Co (basic rock compared to felsic rock enriched) are employed to understand the relative contributions of felsic and basic origins in shales derived from diverse tectonic locations [27, 28]. Akinyemi et al. [19] reported the paleoenvironment reconstruction of the outcropped Matrichtian shale along Auchi-Igarra road using redox sensitive inorganic elements and mineralogical approach. However, the provenance, tectonic setting and paleoweathering of the Maastrichtian Mamu Shale Formation exposed at Auchi-Igarra Road, Edo State in Nigeria is hitherto not documented in the literature. Therefore, the main objective of the present study is to identify the source rock characteristics (i.e. provenance), source area weathering, and tectonic background through primary and immobile trace elements.

## **2. Geological setting**

The Anambra Basin is located from longitudes 6.30 E to 8.00 E and from the latitudes 5.00 N to 8.00 N. It is a syncline that trends from NE to SW as part of Central African Rift System. The basin was established in reaction to the widening and settling of major crustal blocks through the Early Cretaceous plate partitioning of South America and Africa [29]. The movements were restarted through additional activity on the Lower Tertiary plate subsequent to the alternation in the Upper Cretaceous rift. The proposed rift model was based on the evidence gathered by geomorphic, stratigraphic, structural, and paleontological research in literature [30–32]. The development of the basin denotes the third evolutionary sequence of the Benue Trough and its related basins when the Abakaliki Trough was elevated to the Abakaliki Anticlinorium whereas the Anambra Platform was transformed into the Anambra Basin [33, 34]. This transformation gave way to the westward transposition of the depositional axis of the troughs.

The sedimentation trend of the Anambra Basin is categorized by unstable depocentres. The basin consists of nearly 6 km of dense Cretaceous/Tertiary sediments *Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*

and is the structural connection from the Cretaceous Benue Trough to the Tertiary Niger Delta [35]. The basin is a portion of the lower Benue Trough comprising the post-deformational Campanian—Maastrichtian to the Eocene sedimentary strata. Sedimentation in the basin started with the Campano—Maastrichtian marine and paralic shales of the Enugu and Nkporo formations superimposed by the coal seams of the Mamu Formation. The fluivo-deltaic sandstones of the Ajali and Owelli sandstones are located in the Mamu Formation, which mostly comprises of its equivalents. The marine shales of the Imo and Nsukka formations were deposited in the Paleocene; superimposed by the tidal Nanka sandstones of the Eocene age. The downdip towards the Niger Delta, Akata Shale and Agbada Formation account for the Paleogene equivalents of the Anambra Basin [1].

## **3. Materials and method**

## **3.1 Sampling method**

The outcrop of the Maastrichtian shale is located at coordinates 07°05′.071″ N and 06°14′.826″ E at 162.72 m above sea level (**Figure 1**). About 500 g of each sample was obtained at a sequence interval of 0.2 m from the shale. After collection, the samples directly stored in zipped lock polyethene bags for preservation at ambient temperatures. Next, the shales were oven dried at 60°C for 12 h. On cooling, the each sample was milled into a homogeneous powder using an agate ball mill. Next, the crushed shales characterized by scanning electron microscopy/energy dispersive spectroscopy (SEM/EDS) technique. Geochemical analysis was performed by X-ray fluorescence (XRF) Spectroscopy and Laser Ablation-Induced Coupled Plasma Mass Spectrometry (LA-ICPMS).

## **3.2 X-ray diffraction analysis**

The nine representative samples collected from the Maastrichtian shale of Mamu Formation were characterized to determine bulk mineralogy by X-ray diffraction (XRD). A detailed analytical procedure is reported in Akinyemi et al. [19].

**Figure 1.** *Map showing the location of the study area.*

## **3.3 SEM/EDS analysis**

The surface morphology of the nine samples was determined by scanning electron microscopy (SEM). The SEM is an FEI Nova NanoSEM (Model: Nova NanoSEM 230). The EDS analyses were determined at 20 kV and 5 mm working distance. The EDS detector is an Oxford X-Max (large area silicon drift detector) operated with the INCA- (INCAmicaF+ electronics and INCA Feature particle) analysis software.

## **3.4 XRF and LA-ICPMS analyses**

The composition of the metal oxides in the nine samples acquired at various heights in the Formation was determined by X-ray fluorescence (XRF) spectroscopy. The major oxides detected during XRF were; SiO2, TiO2, Al2O3, Fe2O3, MgO, MnO, CaO, Na2O, K2O, Cr2O3 and P2O5. However, the composition of the trace elements in the samples was examined by LA-ICP-MS. The trace elements determined include; Ni, Cu, Zn, Ga, Rb, Sr, Y, Zr, Nb, Co, V, Pb, Th, U, Ti, Cr, Ba, La, Ce, Nd and P). The XRF and LA-ICP-MS tests were performed at the elemental analysis laboratories of the Stellenbosch University in South Africa. The techniques for sample preparation and ICP-MS analyses are as described in Akinyemi et al. [19]. The precision of the findings is presented as comparative standard deviation (in %) which is 5% for most of the elements analyzed with the LA-ICP-MS technique. The geochemical results from XRF were regularized to 100% volatile-free before plotting the data.

## **3.5 Loss on ignition determination**

The loss of ignition (LOI) was examined through the experimental techniques reported in Ojo [36]. The LOI was determined by first weighing an empty porcelain crucible, before adding 1 g of the dry mass of each sample to the crucible. Next, each sample was oven dried at 120°C for half an hour (30 min). The crucible and the sample were subsequently transferred to a furnace pre-heated to 1000°C for about 45 min. On completion, the samples were cooled in desiccators and weighed repeated until a constant weight was reached.

## **4. Results and discussion**

## **4.1 Mineralogy and surface morphology**

The base of the Mamu Formation is mainly dominated by quartz and kaolinite with minor traces of hematite, as described in literature [19]. The hematite in the base of the shale profile shows the oxidizing diagenetic setting for deposition. However, the upper portion of the profile is characterized by quartz and kaolinite with minor quantities of halloysite and grossite. **Figures 2** and **3** present the results of the SEM micrographs of the samples taken at the basal and upper part of the lithosection of the outcropped Mamu Shale.

The SEM investigation of samples taken at the basal and the upper part of the outcropped shale section show a mixture of sizes and morphologies of kaolinite in all the samples. As shown in **Figure 2a**, the quartz particles are spherical to rounded and exfoliated. The kaolinic particles are rolled with rough edges and some individual' particles have lamellar shape indicating a terrigenous origin (**Figure 2b** and **c**).

*Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*

#### **Figure 2.**

*SEM photomicrographs of samples taken at basal part of outcropped shale of Mamu Formation. (a) Spherical quartz particle, rounded corners, and exfoliation, (b) rolled and rough edged kaolinite particles and (c) lamellar kaolinitic crystals.*

Bortnikov et al. [37], reported that terrigenous kaolinite is consists of lamellar particles and remains of differently preserved vermicular crystals. Kaolinite particles are arranged face to face and individuals show well defined crystalline pseudo-hexagonal and rough edges indicating detrital origin (**Figure 3b** and **c**). **Figure 3c** shows the face to face arrangement patterns of kaolinite particles in which larger platelets are surrounded by smaller ones suggesting bimodal origin (i.e. both terrigenous and authigenic varieties). Therefore, structural, and morphological growth of kaolinite in the outcropped shale samples of Mamu Formation is attributed to mechanical disintegration during transportation and redeposition.

## **4.2 Bulk composition and geochemical classification**

The chemical composition and ratios of selected major oxides of the studied samples are shown in **Tables 1** and **2**, respectively. The major oxide components are SiO2,

#### **Figure 3.**

*SEM photomicrographs of samples taken at upper part of outcropped shale of Mamu Formation. (a) Authigenic quartz particle and face to face arrangement of kaolinite particles, (b) face to face arrangement patterns of larger platelets of kaolinite surrounded by smaller ones and (c) pseudo hexagonal and rough edges kaolinite particles.*

Al2O3 and Fe2O3 while other oxides occurred in minor quantities. The average contents of SiO2, Al2O3 and Fe2O3 are 64.84 wt%, 19.79 wt% and 2.22 wt%, respectively (**Table 1**). The ratios of SiO2 to Al2O3 ranged between 1.96 wt.% and 26.95 wt.% with an average value of 5.29 wt.%. The TiO2/Al2O3 ratios varied between 0.04 and 0.08 with an average value of 0.07. The K2O/Na2O ratios ranged from 1.96 to 24.67 with an average value of 16.50 (**Table 2**). The ratios of Fe2O3 + MgO to K2O + Na2O ranged from 1.57 to 14.31 with an average value of 3.31. The plot of log (SiO2/Al2O3) versus log (Fe2O3/K2O), based on Herron [42], clearly shows the studied samples majorly fall within the shale field with one sample within the greywacke field and another in the Fe-sand field (**Figure 4**). This exceptional trend of the two samples is attributed to the relatively high Fe2O3 contents in samples taken at 0.0 m and 0.2 m depths.

The major oxides were compared with the average values of shales worldwide [43], Average North American Shale [44, 45], Average Post-Archaean Australian Shale, and Upper Crust (data from Taylor and McLennan [46]). As observed, the average SiO2, Al2O3, and TiO2 in the studied samples is higher than Average World Shale, PAAS, NASC, Upper Crust [45]. Conversely, the average Fe2O3, CaO, MgO, MnO, Na2O, P2O5 and K2O contents in the studied samples is below the Average World Shale, PAAS, NASC, Upper Crust (**Table 3**) [45]. The average trace element such as Ba, Cu, Ni, Zn, and U in the studied samples is lower than shales from various regions of the globe


**Table 1.**

*Bulk chemical composition of Maastrichtian Mamu shale sequence.*

## *Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*


**Table 2.**

*MIA = 2\*(CIA − 50) [41].*

*Ratios of major oxides in the Maastrichtian Mamu shale sequence.*

*Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*

#### **Figure 4.**

*Chemical classification of the Mamu shale sequence based on log (SiO2/Al2O3) vs. log (Fe2O3/K2O) diagram of Herron [42].*


*Average Shale Worldwide [43]; Average Post-Archaean Australian Shale [48]; NASC = Average North American Shale (data from [44]); UC = Upper Crust (data from [48]); Turekan and Wedephol [47].*

#### **Table 3.**

*Major oxides of Maastrichtian Mamu shale sequence compared with worldwide shales.*

(**Table 4**). On the other hand, the average concentrations of Ce, Co, Nb, Rb, Sr, V, Y, Zr, Th, Cr, La and Nd in the studied samples is higher than shales from various areas of the globe (**Table 4**).


*Average Shale Worldwide [43]; Average Post-Archaean Australian Shale [48]; NASC = Average North American Shale (data from [44]); UC = Upper Crust (data from [48]); Turekan and Wedephol [47].*

#### **Table 4.**

*Comparison of average trace element contents with other worldwide shales.*

## **4.3 Source area weathering**

Several authors have recommended that the chemical composition of clastic sedimentary rocks is mainly reliant on the composition and weathering settings in the area of the source rock [49, 50]. The study by Nesbitt and Young [50] examined the extent of weathering of a clastic sedimentary rock by computing the chemical index alteration (CIA) which is defined as:

$$\text{CIA} = 100 \times \left(\frac{Al\_2\text{O}\_3}{Al\_2\text{O}\_3 + CaO^\cdot + Na\_2\text{O} + K\_2\text{O}}\right) \tag{1}$$

This weathering index is mostly valid when Ca, Na, and K declines with increasing weathering intensity [51]. In Eq. (1), CaO\* is the concentration of CaO fused in the silicate portion of the shales examined [40]. However, the CaO correction from *Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*

the carbonate influence was not performed for the samples examined in this study due to lack of CO2 data. Therefore, the computation for CaO\* from the silicate portion requires adopting Bock et al. [52] hypothesis. Based on the assumption, the CaO values are only valid when CaO ≤ Na2O. However, if CaO > Na2O, it is probable that the CaO concentration is equivalent to Na2O [52]. The outlined technique is the basis for the measure of the weathering intensity and the ratio of the lesser aluminous compound to feldspar [53]. The Chemical Index of Weathering (CIW) proposed by Harnois [39] is similar to the CIA except for the exclusion of K2O in the equation:

$$CIW = \text{molar} \times \left(\frac{Al\_2\text{O}\_3}{Al\_2\text{O}\_3 + CaO + Na\_2\text{O}}\right) \tag{2}$$

For CIA and CIW, the values are deduced in the similar to the unweathered upper continental crust (~50) and for greatly weathered constituents (~100) with comprehensive elimination of the alkali and alkaline-earth metals [26, 54, 55]. Typically, small values of CIA (50 or less) may reflect cool and/or dry conditions [40]. In this study, the values of CIA for shale samples ranged from 91.75% to 95.57%, or 94.57% on average. Similarly, the values of CIW varied between 95.60% and 99.67%, or 99.13% on average. The CIA and CIW standards for the examined shale sequence indicate highly weathered source constituents. This observation is corroborated by the previous study by Ejeh [20].

The chemical weathering intensity is typically computed according to the Plagioclase Index of Alteration [40] in molecular proportions:

$$PIA = \text{molar} \times \left(\frac{Al\_2\text{O}\_3 + K\_2\text{O}}{Al\_2\text{O}\_3 + \text{CaO}^\* + Na\_2\text{O} - K\_2\text{O}}\right) \times 100\tag{3}$$

The term CaO\* represents the CaO residing exclusively in the silicate portion. The unweathered plagioclase typically has a PIA value of 50. In this study, the PIA for the shale samples ranged from 95.40% to 99.67% with an average value of 99.08%, which indicates highly weathered source constituents.

The Mineralogical Index of Alteration (MIA) is a weathering index computed from the equation [41];

$$\text{PIA} = \text{2} \times \text{(CIA} - \text{50)}\tag{4}$$

The MIA values from 0 to 20% are designated as incipient i.e. just starting, 20–40% (weak), 40–60% (moderate), and 60–100% as strong to a great degree of weathering. The MIA values for shale samples examined ranged from 91.19% to 99.34%, with an average value of 98.25%. Therefore, the MIA for shales showed a great amount of source weathering constituents.

**Figure 5** shows that the studied samples plots are near the "A" vertex above the upper continental crust (UCC) line, which indicates a high extent of weathering. Nesbitt et al. [49] used the ternary diagrams of Al2O3-(CaO + Na2O)-K2O (the A-CN-K), and Fe2O3 + MgO-(CaO + Na2O + K2O)-Al2O3 (the A-CNK-FM) to deduce weathering trends. On both the A-CN-K and the A-CNK-FM diagrams in **Figures 6** and **7** respectively, all the sediments indicated an extreme weathering history. The studied samples plot evidently suggest different contents of Al2O3, CaO, Na2O, and K2O in a region examined compared to the Average World Shale, PAAS, NASC, and UC indices. The studied samples plot near the high contents of Al2O3 suggests a relatively high intensity of

*Ternary diagram showing the weathering trend of the studied samples (all in molar proportions); Al2O3- CaO + Na2O-K2O (A–CN–K). Fields from Gu et al. [56].*

#### **Figure 6.**

*Al2O3-(CaO + Na2O)-K2O plot of sediment samples (after [49, 50]), compared to data for post-Archean average shale (PAAS) and upper crust (UC) given by Taylor and McLennan [48]; and north American shale composite (NASC) given by Gromet et al. [44].*

weathering. This implies that substantial content of the alkali and alkaline earth elements were detached from the shales in this study [57].

## **4.4 Chemical maturity and paleoclimatic condition**

Suttner and Dutta [58], suggested the plot of SiO2 versus Al2O3 + K2O + Na2O to infer the paleoclimatic condition of the source region. The studied samples mainly fall within the semi-arid condition at the source area (**Figure 8**). Therefore, the prevalent dry settings of the source region will slow down the weathering process and thereby impede chemical maturity.

*Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*

#### **Figure 7.**

*Triangular Al2O3-(CaO + Na2O + K2O)- Fe2O3 + MgO plot of the current sediment data (after [49, 50]) in comparison with post-Archean average shale and upper crust (data from [48]) and north American shale composite (data from [44]).*

#### **Figure 8.**

*Chemical maturity and paleoclimate of the Mamu shale sequence expressed by bivariate plot of SiO2 versus Al2O3 + K2O+ Na2O (after [58]).*

#### **4.5 Provenance**

Major element geochemistry could offer empirical evidence on the rock composition, source rock, along with the outcome of sedimentary techniques like sorting and weathering [26]. The outlined properties provide evidence of the source rock attributes and definite patterns of historical sediments [59, 60]. Therefore, it is a common practice to infer the origin of deposits and sedimentary rocks [61–66]. The two variable plots of Na2O versus K2O reveals the studied samples are rich in quartz, which shows felsic sources (**Figure 9**). The ternary diagram shows the plots of the

#### **Figure 9.**

*Bivariate plot of Na2O versus K2O of the Mamu shale sequence showing quartz content, after Crook [67].*

#### **Figure 10.**

*Plot of Na2O + K2O, SiO2/10 and CaO + MgO to illustrate possible affinities of the samples to felsic, mafic, and ultramafic rocks (after [48]).*

studied samples in the SiO2 are distant from the basalts, ultramafic, and granitic regions (**Figure 10**). This submits that the felsic igneous or metamorphic or recycled rocks rich in quartz deposits derivation are evident.

Similarly, the composition of zircon is used to describe the nature and content of source rock [68, 69]. The study by Hayashi et al. [68] recommended that TiO2/ Zr ratios can distinguish the three different felsic, intermediate, and mafic types of source rock. The TiO2 versus Zr plot (**Figure 11**) indicates that the samples examined are mostly plotted in the intermediate field although few lie within the felsic and mafic zones. The origins of a sedimentary rock suite can be computed through the K2O versus Rb ratios, which are mostly identical to the standard Upper Continental Crust values [70]. The Cr/V–Y/Ni ratios could also provide estimations of the specific composition of chromium over other ferromagnesian elements [26, 71].

*Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*

**Figure 11.** *TiO2-Zr plot for the Mamu shale sequence [68].*

**Figure 12** shows the plots of studied samples in the acidic/intermediate composition zone with one sample located in the basic composition zone. The Cr/V ratio describes the enrichment of Cr regarding additional ferromagnesian elements. However, the Y/Ni ratio appraises the connection amongst the ferromagnesian minor elements (denoted by Ni) and the HREE using Y as a substitute [26]. The Y/Ni ratios typically range across values from midway to the felsic calc-alkaline rocks (**Figure 13**). The sediments resulting from ultrabasic origins typically have high Cr/V ratios above 1 and low Y/Ni ratios below 1 [71]. The Cr/V ratio ranged from 0.52 to 0.99, or 0.66 on average. However, the Y/Ni ratio was from 1.1 to 9.6 with an average value of 4.79, which suggests felsic compositions in the source materials.

**Figure 14** reveals that the source rocks for shales examined are Late-Archean. The residues reveal minimal scatter along with trace Cr constituents, which indicates

**Figure 12.** *K2O versus Rb plot. Fields after Floyd and Leveridge [72].*

#### **Figure 13.**

*Cr/V–Y/Ni plots for the sediments showing the lack of ultrabasic sources (after [26]). Ultrabasic field of sands derived from ultrabasic rocks, after Ortiz and Roser [73].*

#### **Figure 14.**

*Cr–Ni plot for the studied samples showing the plots in the late-Archean field [48] and fractionation from source rocks to the sediments.*

depletion and homogenization could have occurred in the course of transportation or weathering. Floyd et al. [70], applied immovable elements such as TiO2 and Ni to deduce the original lithological structure of rocks. The technique was also employed to separate unformed residues of magmatic origins from standard mature sediments. The studied samples are plotted within the zone of an acidic or felsic source (**Figure 15**). According to Cullers and Berendsen [74], the Th/Co versus La/Co ratios are used to distinguish the source materials of sedimentary rocks. The shale samples examined in this study are plotted mainly in the upper continental crust and one sample each show close proximity to basaltic and granodioritic zone respectively (**Figure 16**). This observation agreed with the previous study conducted by Ogbahon and Olujinmi [76].

#### **4.6 Tectonic evolution**

The discrimination diagrams of major elements can be used to describe or distinguish rocks based on the tectonic setting was suggested by several authors [23, 24, 77]. *Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*

**Figure 15.** *TiO2 vs. Ni plot. Fields and trends fashioned after Gu et al. [56] and Floyd et al. [70].*

**Figure 16.**

*Source rock discrimination diagram for Mamu shale sequence (after [74]), in relation to average values of granites, basalts, granodiorite [75] and upper continental crust [46, 48].*

Roser and Korsch [24] suggested four tectonic discrimination diagrams based on the SiO2 as the x-axis and K2O/Na2O as the y-axis. As shown in **Figure 17**, the studied samples indicated Passive Margins tectonic field. Furthermore, the tectonic discrimination

**Figure 17.** *Tectonic discrimination plot for the Mamu shale sequence (after [24]).*

**Figure 18.**

*SiO2/Al2O3 ratio versus K2O/Na2O ratio plot for Mamu shale sequence. Fields and boundary lines (after Maynard et al. [78]; Roser and Korsch [24]). A1 = arc setting, basaltic and andesitic detritus; A2 = evolved arc setting; ACM = active continental margin; PM = passive margins.*

diagram of K2O/Na2O as the x-axis and SiO2/Al2O3 as the y-axis similarly depicted studied samples in the Passive Margins zone (**Figure 18**). This trend is supported by the previous study done by Ogbahon and Olujinmi [76]. The residues from the passive margin are fundamentally rich in quartz and derived from established continental regions, placed in intracratonic basins or on passive continental boundaries [24].

*Mineralogy and Geochemistry of Shales of Mamu Formation in Nigeria: Effects of Deposition… DOI: http://dx.doi.org/10.5772/intechopen.102454*

## **5. Summary and conclusion**

In this study, the structural and morphological evolution of kaolinite in the samples is attributed to mechanical disintegration during sediment transportation and redeposition. The shales of the Mamu Formation show considerable variation with regards to major oxides, trace, and rare earth elements. The abundant major oxides showed that SiO2, Al2O3 and Fe2O3 constitute more than 86% of the bulk chemical composition. The plot of log (SiO2/Al2O3) versus log (Fe2O3/K2O) indicated that the samples examined are majorly within the shale field. The weathering indices such as CIA, CIW, PIA and MIA indicated highly weathered source materials. Provenance indicated heterogeneous sources for the studied clastic sediments. The examination of geochemical parameters such as Th/Co versus La/Co, TiO2 versus Ni, Cr/V versus Y/Ni and TiO2 versus Zr suggest the samples could be the result of acidic or felsic sources and not intermediate or basic source rocks. The Cr versus Ni plots indicated the studied samples are Late Archean shales. In the provenance discrimination diagrams based on major and immobile elements, the outcropped shale samples show geochemical markers in agreement with the source rocks of intermediate structure, whereas the tectonic discrimination diagrams indicate Passive Continental Margin field.

## **Author details**

Segun A. Akinyemi1 \*, Olajide F. Adebayo1 , Henry Y. Madukwe1 , Adeyinka O. Aturamu1,2 and Olusola A.OlaOlorun1

1 Geology Department, Ekiti State University, Ado Ekiti, Nigeria

2 Geology Department, University of Leicester, Leicester, UK

\*Address all correspondence to: segun.akinyemi@eksu.edu.ng

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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## **Chapter 4**

## Petroleum Geochemistry

*Mei Mei and Barry Katz*

## **Abstract**

Petroleum geochemistry has entered its second period of growth. The first period, largely associated with conventional oil and gas, occurred in the 70s and 80s when the classic works on source rock characterization, biomarkers, depositional systems, and petroleum generation, including kinetics and basin modeling were the focus. The second period began slightly after the turn of the century as a consequence of the "unconventional resource" revolution and the interest in distressed resources developed, the focus turned to non-hydrocarbon contaminants, new interest in hydrocarbon expulsion and retention, identification of tight rock pay zones, and the development of organic porosity. This chapter will discuss source rock characterization and formation, petroleum generation, expulsion, and retention, correlation among hydrocarbon accumulations and to their source rock(s), and organic porosity.

**Keywords:** source rock, characterization, deposition, petroleum generation, retention, expulsion, migration, geochemical inversion, correlation, petroleum geochemistry, oil, biomarker, organic porosity

## **1. Introduction**

There are five components to a petroleum system - hydrocarbon charge, reservoir, seal, trap, and overburden [1]. When assessing exploratory risk each of these elements is directly assessed except for overburden, which is incorporated into the different risk elements (e.g., overburden is incorporated into charge through thermal maturity, seal and reservoir through porosity and permeability reduction associated with compaction). The absence of any of these elements brings the chance of exploratory success to zero. Hydrocarbon charge is considered the most important component of any petroleum system evaluation [2] because there is no alternative. In frontier regions and play extensions, post-drill assessments have indicated that the absence of hydrocarbon charge is a disproportionate cause of exploratory failure [3, 4]. Significant improvement in exploration efficiency was reported when geochemistry was taken into consideration as compared to simply assessing opportunities by trap size alone [5]. Fundamental to understanding hydrocarbon charge is clarity on its components which include the source rock presence and quality, generation process (maturation), and alteration (e.g., biodegradation, thermal cracking, phase segregation).

The importance of the organic matter to the formation and accumulation of hydrocarbons was fundamentally established by (1) the identification of porphyrins, a chlorophyll derivative, in shales, coals, and crude oils [6], and (2) the observation

of threshold level of total organic carbon (TOC), approximately 1.5% as a mean of petroliferous basins, rather than the 0.35% of non-petroliferous basins of the Russian Platform [7].

Since these works, and especially over the past five decades, there has been considerable advancement in the foundational understanding of hydrocarbon charge. There have effectively been two major periods of advancement in petroleum geochemistry. The first growth episode occurred, in part, as a result of advances in analytical methods as well as insights into the controls on source rock development and the processes of hydrocarbon generation, expulsion, migration, and alteration. During this period the application of gas chromatography/mass spectrometry (GC/MS) became routine for the assessment of source rock depositional setting and thermal maturity; and basin models became commonplace, requiring an understanding of the kinetics of hydrocarbon generation. The second growth period came with the increase in the importance of self-sourced petroleum systems and tight rock resources. During this recent phase, the focus has been on the identification of landing zones, hydrocarbon expulsion and retention, hydrocarbon cracking, and the development of organic porosity.

This overview discusses the identification, characterization, and formation of hydrocarbon source rocks, the generation process, the characterization of produced fluids including post-accumulation alteration processes, hydrocarbon migration, and establishing genetic relationships among hydrocarbon accumulations, and to their source rock(s), and organic porosity.

## **2. Source rock identification and characterization**

It is important to establish a consistent definition of source rock. A source rock is a rock that contains sufficient quantities of organic matter that after having achieved the appropriate thermal maturity will generate and expel sufficient quantities of hydrocarbons to result in an accumulation. At this point issues of commerciality are not considered because they are dependent on logistics, the presence of prior infrastructure as well as commodity price.

Petroleum source rocks are atypical and are not uniformly distributed either stratigraphically or spatially [8]. The mean value for organic carbon in fine-grain sedimentary is ~0.7 wt.% with a standard deviation of 0.3 wt.% as established using a statistical approach and more than 15,000 fine-grained rock samples worldwide [9]. It was then noted that source rocks should display above-average TOC levels establishing a threshold TOC of 1.00 wt.% (**Figure 1**). However, a review of data from a number of world-class source rocks such as the Kimmeridge Clay (North Sea Basin), Green River Formation (western United States), Pematang Formation (Central Sumatra Basin, Indonesia), Bucomazi Formation (Lower Congo Basin, Angola), Hydria-Hanifa Formation (Saudi Arabia), Maykop Formation (South Caspian Basin, Azerbaijan), Shublick Formation (Alaska) and Kazhdumi Formation (Mesopotamian Foreland Basin, Iran), all contained significant stratigraphic intervals where organic carbon contents exceeded several weight percent organic carbon. This indicates that source rocks, in fact, typically contain TOC levels that significantly exceed the 1.0% wt.% TOC threshold.

It has also been suggested that there is an upper limit for TOC that limits a source rock's effectiveness. It is suggested that at TOC levels of 12 to 15 wt.%, oil is retained within the source rock limiting its effectiveness [10]. This upper limit may also partially explain why most coals do not act as an effective source [11].

#### **Figure 1.**

*Global distribution of total organic carbon within fine-grain sedimentary rocks. Insert represents the organic carbon measured at the type locality of the Kimmeridge clay (United Kingdom), after Bissada 1982 [9].*

It was, however, established early that not all organic matter is the same with respect to hydrocarbon generation and that the assignment of source rock potential based on organic carbon is insufficient. Similar quantities of organic matter can have yields that range over several orders of magnitude depending on the type of organic matter and the thermal maturity (**Figure 2**). This question of yield was approached using the total generation potential (free hydrocarbons + generatable hydrocarbons: S1 + S2) as determined using Rock-Eval pyrolysis. A threshold of 2.5 mg HC/g rock [9] was considered for a possible oil-prone source rock (**Figure 3**). This threshold was established as outlined above for organic carbon. A physical reason for this threshold

#### **Figure 2.**

*Comparison of residual generation potential (S2) of samples with similar total organic carbon content. Note that for the same TOC, hydrocarbon yield can vary by order of magnitude.*

#### **Figure 3.**

*Global distribution of total generation potential of fine-grain samples containing a minimum of 0.5 wt.% TOC. Insert represents the total generation potential measured on samples greater than 0.5 wt.% TOC at the type locality of the Kimmeridge clay (United Kingdom), after [9].*

also appears present. This reported threshold is consistent with the previously reported minimum of 825–850 ppm hydrocarbons thought to be required for expulsion to occur [10]. A rock having a total generation potential of ~2.5 mg HC/g rock as it approaches the main stage of hydrocarbon generation approaches a free hydrocarbon content consistent with this threshold. Thresholds for possible gas-prone source rocks are less well-defined, in part, because of their different expulsion mechanisms [12]. Oil expulsion requires that the pore network becomes saturated, and the rock becomes over-pressured. In contrast, gas expulsion can occur through diffusion which simply requires a concentration gradient once the sorption capacity of the source is achieved [13] or in solution within a liquid hydrocarbon phase.

The atomic H/C and O/C ratios were used to define three primary kerogen types as an explanation for the observed differences in hydrocarbon yield and product character [14]. This van Krevelen diagram has been modified to provide more specific guidance on product characterization (i.e., oil yield) [15] and visualized here in **Figure 4**.

Type I kerogen was defined using the Green River Formation and algal kerogens and has the greatest hydrocarbon yield for a given mass resulting from the abundance of hydrogen. When mature type I kerogen will yield principally oil with a lesser amount of gas. The kerogen structure contains abundant long-chain hydrocarbons [16]. This type of kerogen is principally derived from algal material and often appears associated with marine and lacustrine carbonate depositional systems.

Type II kerogen displays lower atomic H/C and higher atomic O/C ratios than Type I organic matter. It produces both oil and gas upon maturation and was defined using the Schistes Carton Formation (lower Toarcian, Paris Basin, France) and Silurian shales of North Africa. The kerogen structure is much more diverse than Type I kerogen due to the diversity of the organic material that led to its development, which includes algal material, plant cuticle, spores, pollen, and resin, which may be microbially reworked. Although often considered to represent a marine depositional system, such kerogen was found to also dominate in siliciclastic-dominated lacustrine systems, such as the Pematang Formation of Central Sumatra.

As implied, the difference in organic matter type between a clay-rich mudstone and a carbonate source rock rest with one of the foundational differences in the development of these two rock types. Carbonate rocks are generally considered to be autochthonous with both the mineral and organic matter forming at or very near to

**Figure 4.**

*Conventional van Krevelen diagram based on the atomic H/C and O/C ratios. Relative oil and gas yields have been added.*

the depositional site. In contrast, clay-rich mudstones are derived from both inorganic and organic material that is transported to their depositional site, reflecting the provenance of the drainage basin, with the lesser autochthonous contribution.

A subset of Type II kerogen is Type II-S, which contains greater than 6% organic sulfur [17]. This differentiation is important because the C-S bond is weaker than the C-C bond and generation proceeds at lower levels of thermal maturity, producing products with greater amounts of asphaltenes and resins.

Type III kerogen was defined using Cretaceous shales from the Douala and Western Canadian Sedimentary basins. It has lower H/C and more elevated O/C ratios than Type II kerogen. It produces the lowest amounts of hydrocarbons per unit mass and yields principally gas. The kerogen structure is envisioned to be dominated by interconnected aromatic rings, with shorter chain hydrocarbon elements. Although this type of organic matter is often associated with vitrinite (a wood derivative) it may also be derived through the poor preservation (oxidation) of marine organic matter.

As a consequence of thermal maturation and the generation of products including organic acids and hydrocarbons both the atomic H/C and O/C ratios decrease. In the case of Type I kerogen, there is a rapid decrease in the atomic H/C ratio and a modest decrease in O/C ratio with increasing thermal maturation. In contrast, there is a rapid decrease in the atomic O/C ratio and a modest decrease in the atomic H/C ratio for Type III kerogen. These changes result in an inability to differentiate among the different kerogen types using their elemental composition at more advanced levels of thermal maturity and alternative means are required for such kerogens.

Subsequently, a fourth kerogen type has been defined, which represents residual organic matter [18]. It displays very low atomic H/C ratios and highly varied atomic O/C ratios. This material is largely inert and incapable of yielding any significant

amount of hydrocarbons. It is dominated by inertinite. This material commonly forms through prolonged transport, very slow sedimentation rates leading to long exposure times, or forest fires.

The aforementioned approach to organic matter characterization requires the isolation of kerogen from the rock matrix. This is a time-consuming process that utilizes hydrochloric and hydrofluoric acids as well as requiring relatively large sample volumes. An alternative was proposed that was rapid and required only grinding as sample preparation and did not require large sample volumes. This method was Rock-Eval pyrolysis, where the sample was heated in an inert atmosphere. Two of the measured parameters are used to calculate the hydrogen index (S2\*100/ TOC) and the oxygen index (S3\*100/TOC, where S3 represents the CO2 yield) are substituted for the atomic H/C and O/C ratios, respectively (**Figure 5**).

Although these indices have become routinely accepted for kerogen characterization there are some limitations that are known to exist and should be considered when interpreting the data. For samples with very high generation potentials, the use of the standard sample size may result in the saturation of the flame ionization detector, which produces an apparent reduction in S2 yield and consequently the hydrogen index making the sample appear more gas-prone than would be implied if elemental analysis on isolated kerogen was used. In addition, several studies have shown that there are mineral matrix effects. These effects are especially notable for samples with lower organic carbon contents. It is suggested that for samples with less than 2 wt.% TOC hydrocarbons are retained by the rock matrix, especially in clay-rich samples. This retention reduces the apparent generation potential and the derived hydrogen index [19]. It was also observed that the oxygen index was sensitive to the presence of carbonate minerals, especially siderite. These effects cause the organic matter to appear more gas-prone than in kerogen isolates. Alternative means of correcting the oxygen index for the presence of siderite-derived CO2 have been proposed [20, 21], however, these approaches alter the value proposition, which was a rapid and simple means to assess generation potential, organic matter type, and thermal maturity.

#### **Figure 5.**

*Modified van Krevelen diagram based on the rock-Eval parameters the hydrogen and oxygen indices. Arrows represent changes in parameters as a function of increasing thermal maturity, increasing carbonate (especially siderite) content, and decreasing organic carbon.*

**Figure 6.**

*Alternate means of characterizing organic matter utilizing the hydrogen index and Tmax. Arrows represent changes in parameters as a function of increasing thermal maturity and decreasing organic carbon.*

An alternative approach to organic matter characterization without the possible oxygen index complication relies on the relationship between the hydrogen index and Tmax (**Figure 6**). This approach is still limited at lower TOC values.

Alternative pyrolysis approaches have been developed that provide additional information. The first adds gas chromatography to the pyrolysis unit and is known as Py-GC. This analytical approach provides a more detailed understanding of the products generated beyond a simple assessment of oil- and gas-proneness [22, 23]. A chromatogram of isolated kerogen through Py-GC with vented free hydrocarbons below 320°C (equivalent to Rock-Eval S1 peak) and then pyrolyzed up to 600°C is produced from what essentially was the Rock-Eval S2 peak (**Figure 7**). These chromatograms provide information on such geochemical properties as waxiness, relative abundance of naphthenes, and aromatic compounds. The relative abundance of C1-C5, C6-C14, and C15+ in the Py-GC was used to assess the oil and gas-proneness of different types of kerogens [23].

Another thermal extraction-pyrolysis innovation has been developed, which has a more complex temperature ramp and is designed to better characterize the free hydrocarbons present in the rock, where the free hydrocarbons are broken down into four fractions (thermal extraction <350°C), representing C4-C5, C6-C10, C11-C19, and C20-C36 (the four oil fractions in **Figure 8**). The K-1 peak in **Figure 8** represents pyrolysis of kerogen at 350–600°C. The Petroleum Assessment Method (PAM) was developed to better assess the nature of the hydrocarbons present in self-sourced petroleum systems [24].

Part of the assessment of the validity of a geochemical assessment is a determination as to whether a sample has been stained (natural processes) or contaminated (anthropogenic processes). This assessment is based on the relationships between the abundance of free hydrocarbons (S1) and the total organic carbon content (**Figure 9**), and the relationship between Tmax (temperature of maximum hydrocarbon yield)

**Figure 7.**

*Pyrolysis-gas chromatograms of A - Green River Formation (Utah, United States); B - Kimmeridge Clay (United Kingdom); C - Talang Akar Formation (Indonesia); D - Banquereu Shale (Atlantic Canada).*

**Figure 8.** *Representative PAM pyrolysis of Devonian Shale (Western Canadian Basin).*

*Petroleum Geochemistry DOI: http://dx.doi.org/10.5772/intechopen.104709*

#### **Figure 9.**

*The relationship between total organic carbon and S1 yield is used to define the presence of staining or contamination.*

#### **Figure 10.**

*The relationship between Tmax and the production index is used to define the presence of staining or contamination.*

and the transformation ratio (S1/(S1 + S2); **Figure 10**). These assessments do not differentiate between natural and anthropogenic hydrocarbons additional analyses would be needed for this differentiation.

The S1\*100/TOC (OSI; oil saturation index) ratio was proposed for identifying potentially productive zones, with values greater than 100 mg HC/g TOC being zones of interest [25]. This approach is essentially limited, however, to wells not drilled with an oil-based drilling fluid system.

There has been some recent work that has also led to questions on the validity of source rock assessment and characterization when organic-based drilling fluids are used. Organic-based drilling fluids are becoming more commonly used because of their greater stability at higher temperatures and improved hole stability when shales are water-sensitive [26]. It was reported that the often-used solvent pretreatment of

contaminated samples does not permit an assessment of the original in situ characters of the rock [27]. The reported organic carbon, generation potential, hydrogen, and oxygen indices were all impacted by the contamination by the drilling fluid and the solvent extraction of the contaminated samples.

## **3. Source rock depositional controls**

As a consequence of the uniqueness of petroleum source rocks, it has been generally accepted that they form under somewhat distinct sedimentary conditions. It was suggested that nearly half of the known source rock systems lack modern analogs (e.g., anoxic epeiric seaways and anoxic oceans [28]). In general, there have been three principal schools of thought on source rock deposition: 1) enhanced organic preservation, often associated with anoxia; 2) enhanced primary productivity, often associated with oceanic upwelling or riverine transport of nutrients; and 3) sedimentation rate, often associated with either rapid removal of the sediment from the various microbial zones or through the concentration of organic matter through a lack of dilution by sediment (i.e., a condensed section). Arguments have been presented to support each as a stand-alone model.

The enhanced preservation model is largely based on the argument that anoxic environments, where oxygen consumption exceeds supply, favored preservation [29]. Such settings are associated with stratification, reduced circulation, water body isolation, or estuarine flow. The primary argument for this was the presumed relative inefficiency of anaerobic processes, which slows decomposition [30]. However, activity levels of anoxic and oxic microbial communities have been shown to display similarities [31]. It appears that the absence of meibenthos and macrobenthos may be more important than microbial rates because they are more efficient consumers of organic matter compared to microbes [32] and also provide a means to irrigate the sediment through bioturbation [33]. Similarly, the absence of alternative oxidizers such as sulfates also leads to more efficient preservation. This limits the source rock potential of evaporitic settings once gypsum precipitation is initiated, and sulfate reduction may occur. Another argument for enhanced preservation was associated with settling or exposure time within the oxic portion of the water column. It was observed that there were order of magnitude reduction in organic matter preservation efficiency from the shelf to the central ocean basin as a result of exposure time [34]. Further reports suggest that settling time could be reduced through the pelletization process, where the increase in particle size and the incorporation of mineral matter increased the settling rate with added protection coming from the mucilaginous cover that the pellets have after passing through the digestive system [35]. It should be noted, however, that stratification may limit nutrient renewal and lead to oligotrophic conditions, suggesting limited autochthonous input and that under such circumstances terrestrial input may be favored.

The primary productivity model was based on the general concept that elevated amounts of organic matter would be incorporated into the sedimentary record if productivity was high [36]. Higher levels of productivity are associated with regions of nutrient renewal such as coastal upwelling, seasonal water body turnover (which is especially common in lake systems and temperate water bodies), as well as riverine input. Numerous publications attempted to highlight areas of high productivity through time through paleoclimate and paleocirculation modeling (e.g., see [37]). In the modern ocean, there are numerous regions of high productivity, however, that

### *Petroleum Geochemistry DOI: http://dx.doi.org/10.5772/intechopen.104709*

lack significant organic carbon in the sediment. This is clearly documented in the Southern Ocean where an intense upwelling system has been established but is also a region where freshly-oxygenated bottom waters are present. Here the sediment appears dominated by siliceous tests and TOC is minimal, (typically below 1.0 wt.%) as a result of organic carbon's brief residence time of 15 to 150 years [38]. Attempts to correlate regions of modeled high productivity have had limited success. In part, this is because of factors beyond nutrient availability that influence productivity such as turbidity. For example, the suspended load of the Mississippi River results in limited light penetration at the river's mouth. The region of elevated productivity is thus shifted further offshore to where the sediment has salted-out.

The discussion on the role of sedimentation rate follows two paths. Early arguments suggested greater potential for organic matter preservation when sedimentation rate was high [39]. It was suggested that rapid sedimentation would reduce the time spent within the various microbial zones ranging from oxidation through sulfate reduction and eventually methanogenesis. This concept appears supported by the positive correlation between sedimentation rate and total organic carbon [40, 41]. The specific relationship appears to differ among lithologies. However, when the sedimentation rate exceeds approximately 20 m/MY, the organic carbon content begins to decrease as a result of dilution by sediment. An increase in carbon content with an elevated sedimentation rate can only occur if the level of primary productivity increases. In contrast, it's suggested that source rocks are associated with condensed sections, where dilution by sedimentary material has been minimized. An often-cited example of a condensed section source rock is the Shublick Formation in Alaska [42], which also appears to be associated with elevated productivity as suggested by the presence of phosphorites [43]. Not all sediment starved areas develop oil-prone source rocks. It was reported that for a condensed section deposited under oxic conditions such as the Upper Jurassic/Lower Cretaceous of SE France the section is bioturbated and TOC values are less than 0.25% [44]. The influence of sedimentation rate was also noted as part of the preservation model, where more oil-prone material was associated with higher sedimentation rates and inert material was preserved with slow sedimentation rates [29].

In addition to the three working models, it is also important to understand that the reactivity of organic matter is not uniform. It was noted that under oxic conditions planktonic material would degrade more rapidly than the remnants of vascular plants because of chemical differences [38]. Algal amorphous material was easier

#### **Figure 11.**

*Workflow to assess the probability of source rock presence and quality based on primary productivity, preservation potential, and sedimentation rate [46].*

to decompose than structured organic matter [45]. This was, in part, a result of the greater surface area of amorphous organic material.

It was reported that the three single factor models proposed were insufficient and that a more robust model requires the integration of the three taking into consideration the interplay among them (**Figure 11**, [46]).

## **4. Petroleum generation, retention, and expulsion**

Organic matter in source rocks are composed of extractable organic matter (EOM) - bitumen and insoluble organic matter including oil/gas prone kerogen and inert carbon. Under sufficient thermal stress, petroleum is formed incrementally from the decomposition of kerogen and secondary cracking of generated petroleum molecules. This process can be simulated as a series of parallel first-order reactions following the Arrhenius Law. A simple reaction of an initial reactant X with mass x generating a product Y with mass y can be represented by:

 <sup>→</sup> , *<sup>k</sup> X Y* <sup>∂</sup> <sup>∂</sup> =− = ∂ ∂ *<sup>y</sup> <sup>x</sup> kx t t* (1) <sup>−</sup> = *E RT* / *k Ae* (2)

where t is the reaction time, k is the reaction rate, A is the frequency factor, E is the activation energy, and R is the universal gas constant 8.314 J∙K−1∙mol−1.

Laboratory anhydrous and hydrous pyrolysis are used to simulate the processes of natural petroleum generation, retention, and expulsion [23, 47–53]. Burnham systematically documented integration of kinetics and pyrolysis methods to simulate petroleum generation reactions [54]. As shown in **Figure 12**, it is observed that (1) Type I kerogen generates petroleum over a narrower oil window to decompose a more uniform composition; (2) Type II-S kerogen enters oil-window earlier with lower reaction activation energies to breakdown weaker bonds; in contrast to (3) Type II and Type III kerogens that react with an extended and elevated range of reaction activation energies, respectively, to breakdown mixed kerogens with more complex structures.

In most cases, source rocks contain mixed kerogens. Compositional kinetics was developed to simulate a series of reactions from mixed types of kerogens to form complex petroleum compositions and the secondary cracking of products [56–58]. **Figure 13** shows an example of petroleum primary generation and secondary cracking reactions. **Figure 14** shows how these reactions work in a closed system through modeling calibrated with Vaca Muerta Formation data [56]. It shows that (1) asphaltenes and NSO-bearing polar components are formed in the early oil window at 0.5–0.7%Ro, (2) followed by secondary cracking of these components and continuous cracking of kerogens forming saturated and aromatic hydrocarbons in the main oil window at 0.7–1.3%Ro, by then, asphaltenes, NSO-bearing polar components, and large (C15+) aromatic compounds are fully cracked; (3) Beyond 1.3%Ro, large (C15+) saturated and small (C6-C14) aromatic hydrocarbons start cracking, forming light oils (dominant light saturates) and gas hydrocarbons, (4) until 2%Ro where all liquid components are fully cracked to gas and eventually forming dry gas - methane.

*Petroleum Geochemistry DOI: http://dx.doi.org/10.5772/intechopen.104709*

#### **Figure 12.**

*Comparison of activation energy distributions for hydrocarbon generation of four representative different kerogen types (modified after [55]).*


#### **Figure 13.**

*Schematic reaction mechanism of petroleum primary generation and secondary cracking with 17 species (modified after [56]).*

#### **Figure 14.**

*Simulation of petroleum primary generation and secondary cracking in a closed system using calibrated compositional kinetics based on Vaca Muerta Formation data (adapted from [56]).*

Natural petroleum systems in the subsurface are semi-closed systems with not only petroleum generation/cracking reactions, but also retention and expulsion. Kinetics and retention models are incorporated into basin modeling together with

#### **Figure 15.**

*Basin model showing petroleum generation, retention, and expulsion through time and temperature changes, a Vaca Muerta Formation example (adapted from Mei [56]).*

other necessary geochemical and geological inputs to simulate and quantify petroleum generation, retention, and expulsion in subsurface [56, 59, 60]. **Figure 15** shows an example of petroleum generation, retention, and expulsion of Vaca Muerta petroleum system through time and temperature.

Organic matter and clay minerals in source rock have a high sorption capacity for petroleum [61–63]. As shown in **Figure 15** using the Vaca Muerta Formation as an example, the initially high sorption capacity decreases through petroleum generation and sorption with increasing time and temperature. Until the quantity of generated petroleum exceeds source rock sorption capacity, major petroleum expulsion occurs at about 0.85–1%Ro and 120–140°C. This process associates with increasing pore pressure, permeability, and organic porosity. The sorbed components can be further cracked with elevated temperature over time. When thermal maturity is increased to above 1.3%Ro and 160°C, intensive petroleum cracking creates volume expansion and excess pore pressure, which in turn induces rock fracturing and the second stage of major expulsion. Tectonic uplift decreases pressure and temperature, which temporarily stops petroleum generation and expulsion. Continuous burial can result in further cracking and expulsion.

## **5. Petroleum migration**

Within this study, migration is considered the movement of hydrocarbons within a carrier system once they have been expelled from the source rock. This includes the initial movement to the trap as well as any remigration that may occur following the initial accumulation as a result of tectonic movements or the subsequent addition of hydrocarbons.

Hydrocarbon migration is considered the least understood aspect of the petroleum system. This, in part, is a result of our limited ability to observe migration and that we typically see only the results of migration (i.e., the position of the accumulations [64]). Migration is driven by buoyancy, which is controlled by density differences between the migrating hydrocarbons and pore fluids, largely controlled by brine salinity and API gravity [65]. Hydrocarbon migration can occur laterally, vertically, or a combination of the two.

**Figure 16.**

*Structural patterns establish general hydrocarbon migration patterns. Regions of focusing and dispersion are identified.*

Lateral migration occurs in stratigraphic proximity to the source, but over significant distances potentially exceeding 100 km, with accumulations developing beyond the limits of the generative kitchen. A single stratigraphic unit may contain multiple accumulations. The flow paths or migration patterns are, in general, controlled by structural patterns, where hydrocarbons may be focused or dispersed as shown in **Figure 16**. Regions of focus are preferred sites for exploration, while dispersive regions are to be avoided [66]. Flow paths are established at the base of low permeability layers. These flow patterns may change through time as a consequence of structural evolution. Carriers may include permeable beds, fracture networks, and certain unconformity surfaces. Depending on the availability of hydrocarbons an examination of structural patterns may also aid in the identification of migration shadows, as well as opportunities for fill and spill establishing up-dip hydrocarbon charge potential. These migration patterns can be altered by strong water movement and the distribution, character (including variability in permeability), and extent of the carrier beds. Sheet sands provide potentially the longest and least controlled migration patterns, whereas isolated reef bodies such as those of the Michigan Basin provide no continuity and are not effective carriers.

Vertical migration provides a means of transferring fluids across stratigraphic horizons. Accumulations develop above or near the active source. Stacked reservoirs with a common source exist. Surface seepage is common. Although the lateral movement in such systems can be limited, vertical fluid movement can be quite significant, on the order of several kilometers [67, 68].

There are examples where multiple generative kitchens can focus on a common trap. In some cases, these oils may remain distinct, and in others where the oils may mix. Situations exist where sealing faults are present within a structure and no mixing occurs. Such is the case in the Minas field (Central Sumatra, Indonesia) where distinct oils are present on the two sides of the Main Minus Fault Zone.

Migration may be episodic, potentially as a result of fault movement as in the case of deep-water Nigeria, where unaltered oil is introduced into a shallow reservoir where the oil pool has undergone biodegradation [69] or largely continuous and potentially in near real time such as at Eugene 330 Field in Gulf of Mexico [70].

Remigration or dysmigration may result in the loss of hydrocarbons, the repositioning of the remaining hydrocarbons, and changes in oil character (e.g., phase segregation). Remigration may take place as a result of fault movement or structural inversion.

## **6. Geochemical inversion and correlation**

Integrating geochemical inversion, oil to oil and oil to source rock correlations, basin modeling, and regional geology is important to understanding the petroleum system and significantly reducing the risks of petroleum exploration [71, 72]. For clarification, geochemical inversion entails utilizing diagnostic molecular and isotopic characteristics of petroleum collected from seeps, various types of rock samples, and produced fluids to infer (1) the organic-matter type and thermal maturity of the source rock as well as that of the oil or gas at time of generation [72]; (2) the depositional environment (salinity, redox conditions, and lithology) of the source beds [73]; (3) the age of the likely source rocks [74]; (4) accumulation history; and (5) secondary alteration such as biodegradation [75] and migration after expulsion from the source rocks with anomalous or mixing signatures [76–78]. In addition, petroleum to source correlation entails comparison of the geochemical markers in source-rock candidates with equivalent markers in the petroleum to better understand oil origin and migration history. Furthermore, basin modeling entails analyzing the geological and thermal settings for a stratigraphic sequence in a basin to understand the burial and thermal histories of the source bed, and to deduce the probable occurrence of petroleum generation, expulsion, and migration relative to reservoir deposition and trap formation.

To understand whether an oil accumulation is charged from the direct contact source rock or migration from deeper or downdip kitchens, it is critical to understand source rock maturity based on maturity indicators in source rock and calibrated basin modeling. Maturity indicators such as vitrinite reflectance (Ro) and spore-color thermal alteration index (TAI) are commonly measured using microscopic technologies. Uncertainties include (1) indicators that are based on terrigenous organic matter that are commonly deposited in fluvial deltaic environments or transported to marginal marine settings in post-Silurian age. However, oils generated from aquatic kerogen (amorphous alginate and exinite) in marine or lacustrine environments or older source rocks contain limited or no higher plant materials such as vitrinites to measure Ro, or spores and pollen to measure TAI. When bitumen exists, bitumen reflectance can be used to estimate vitrinite reflectance [79, 80], although discrepancies in derived vitrinite reflectance are common using different algorithms. (2) Recycled vitrinite may not experience the same thermal history as the primary kerogen. (3) Even with the same thermal history, different types of kerogen may achieve different extents of maturity via different kinetics. Therefore, it is important to develop direct measurements of thermal maturity for aquatic kerogens and correlate them to the thermal maturity standard Ro [81]. Transmission light spectroscopy and Raman spectroscopy show promising results [82].

In addition, to infer oil origin, identify oil families (oil to oil correlation), and correlate oil with possible source rocks, it is important to analyze and interpret the chemical compositions of oil and bitumen in source rock(s) when available. Crude oil and bitumen are complex mixtures of organic compounds consisting of four major group

### *Petroleum Geochemistry DOI: http://dx.doi.org/10.5772/intechopen.104709*

types: saturated hydrocarbons, aromatic hydrocarbons, resins, and asphaltenes (SARA). Among these compounds are numerous trace components such as biomarkers that are organic compounds derived from ancient living organisms (algae, bacteria, and plants), that can provide source-diagnostic information and relatively resistant to alteration.

To analyze biomarkers in oil and rock samples, SARA group-type separation is used to prepare saturated and aromatic fractions of oils for GC-MS analysis. This sample preparation is required to avoid coelution interference and enhance the sensitivity and accuracy of the analytical method [83–86]. Recent advancements using modern analytical technologies such as GC tandem triple quadrupole mass spectrometry (GC-QQQ-MS/MS) and 2D-Gas-chromatography/time of flight mass spectrometry (GC × GC-TOF) with enhanced analytical resolution enabled simultaneous analysis of diverse trace components in whole oil and minimized volatile loss during sample preparation [87–89]. Sometimes, many of the biomarkers are absent or occur at muchreduced abundance as a result of alteration. New proxies using alteration-resistant compounds such as diamondoids have been investigated [90–92]. Diamondoids are saturated hydrocarbons with cage-like (bridged cyclohexane) structures. They are derived from the structural rearrangements of saturated hydrocarbons catalyzed by Lewis acids (chemical species with an empty orbital that is capable of accepting an electron pair; commonly associated with clay minerals and thermal cracking). Diamondoids are resistant to many alteration processes, particularly stable at higher maturity, and can be used to indicate advanced thermal maturity and cracking.

The analytical results of relative abundances of chemical compositions such as biomarker ratios are commonly used as geochemical indices. The concept, history, and guidelines for geochemical data interpretations with case studies using global samples were systematically documented in the Biomarker Guide [93]. In brief, alteration, source facies, and maturity are interpreted using multiple intact and diagnostic signatures. These interpretations can then be compared with source rock data in a geologic context. **Figure 17** shows examples of geochemical interpretations using GC-MS *m/z* 191 traces of intact terpanes. **Figure 17(a)** and **(b)** are two examples of carbonate sourced oil. **Figure 17(a)** is a low maturity oil from the Triassic carbonate platform in Sicily with characteristics of (1) abundant extended homohopane H35 equal to or more than H34 indicating anoxic water bottom, (2) presence of abundant gammacerane (G) indicating stratified water column which is commonly associated with hypersalinity from carbonate or evaporative settings, and (3) abundant C24 tetracyclic terpane relative to C26 tricyclic terpane indicating a carbonate or evaporite depositional environment. **Figure 17(b)** is a high maturity oil from a Late Jurassic to Early Cretaceous carbonate source rock from Guatemala with characteristics of (1) abundant norhopane (H29) relative to hopane (H30) and (2) relatively higher amount of Ts than Ts indicating carbonate depositional environment. In contrast, **Figure 17(c)** shows a Tertiary oil from the Niger Delta (similar examples see [94]). Specifically, the presence of abundant oleanane (O) indicates terrigenous organic matter inputs in post-Jurassic age and is most associated with Tertiary age, and the stair-step pattern of homohopanes with relatively lower abundance of H35 than H34 indicates a suboxic environment commonly associated with clastic facies. The interpretation above is an example of geochemical inversion. In addition, oil-oil and oil-source correlation are to compare the similarities and differences of geochemical characteristics of oil and source rock. To confirm a genetic relationship, multiple available geochemical characteristics (biomarkers such as terpanes, steranes, and isoprenoids, bulk components such as alkanes and aromatics, and others like elements, isotope ratios, and API gravity, etc.) should be interpreted comprehensively in the context of reasonable geological scenarios.

#### **Figure 17.**

*Examples of GC-MS m/z 191 traces show different oil biomarker (terpane) distribution patterns and indications for different sources (Triassic carbonate oil data is from [89], Jurassic-Cretaceous carbonate oil and Tertiary deltaic oil are from Geomark database).*

## **7. Organic porosity**

With respect to shale, resource plays geochemistry plays a role in establishing source rock potential as well as reservoir potential. Within unconventional reservoirs three porosity types have been characterized: 1) interparticle pores; 2) intraparticle pores; and 3) organic pores. The importance of pore type varies among the different shale plays [95]. Organic porosity is the porosity that has developed or exists with the kerogen, bitumen, and/or pyrobitumen present within the shale play. Organic porosity within plays such as the Barnett Shale (Forth Worth Basin, Texas) and the Longmaxi

### *Petroleum Geochemistry DOI: http://dx.doi.org/10.5772/intechopen.104709*

Formation (Sichuan Basin, China) provides important storage capacity. These pores, because of their small size (often less than 1 μm), are potentially more important for gas systems [96] although organic pores may play a limited role in some oil plays.

Organic pores may be primary, associated with the kerogen's initial structure, or secondary, where it is hosted in bitumen or pyrobitumen as a function of generation and alteration. The assignment to primary and secondary pores may be complicated because the visual differentiation between the kerogen and bitumen is not simple. The means to differentiate between kerogen and bitumen pores were proposed in the literature [97, 98].

Organic pores display multiple morphologies, bubbly, spongy, or fracture/ crack-based pores as shown in **Figure 18** [99]. These forms have different formation mechanisms and associations. For example, the bubbly pore type seems to be largely associated with the oil window and maybe artifacts of water droplets [100]. While cracks and fractures may form through devolitization of solid bitumen [101] or volume changes [102]. The distribution of pores further suggests that the nature of the organic matter, as well as the relationship with the mineral matrix, may play a controlling role. Some of the pores may reflect the initial kerogen character.

Thermal maturity is one of the key controls on organic porosity. The specifics remain poorly understood and are evolving. Porosity has been observed in immature kerogen (e.g., Eagle Ford Shale [100]), with amorphous kerogen being inherently porous, while the cell structure of vitrinite may also provide primary pores. There is some evidence that as the shales enter the oil-window there is a reduction in observed porosity. This is thought to be a result of the generation of bitumen and oil, which fills pre-existing pore space [103], although there are contradictory data that indicates that porosity may begin to develop within the oil-window [100], not at the onset of generation but at a slightly higher thermal maturity (Ro between 0.8 and 0.9% [104, 105]). It was suggested that the pore generation begins with the onset of hydrocarbon generation and increases through the oil-window, with a decreasing rate of organic-pore generation in the gas-window and terminating at 3.5%Ro [106]. These changes in porosity reflect the release of volatiles and the restructuring of the organic matter. It was noted that changes in porosity are not monotonic [107]. It was further suggested that there is an evolution of the porosity type as maturity increases [108]. Pores may coalesce with increasing maturity causing an increase in pore size and complexity. At advanced levels of thermal maturity, there is also some evidence that pores size decreases [109].

#### **Figure 18.**

*SEM photomicrographs of organic matter from the Kimmeridge clay (United Kingdom): A - bubbly organic pores and B - spongy organic pores [99].*

In addition to thermal maturity, organic richness has been considered an important controlling factor in the availability of organic pores. In general, a positive correlation appears to exist between organic porosity and carbon content for TOC levels less than 5.5 wt.% [110]. At the higher levels of organic enrichment, the lack of a correlation may be a result of pore collapse facilitated by greater organic matter connectivity and a less-developed mineral framework. It should also be noted that the greater the organic matter network, the greater the potential for interconnectivity within the organic pore network.

The nature of organic matter is also considered a controlling factor in organic porosity. For example, in humic kerogen, there appears to be little organic pore development beyond what was initially present [111]. In contrast, porosity increases can be observed in solid bitumen. It was suggested that the ratio of bitumen to kerogen was a key factor in determining organic porosity [112]. The greater the solid bitumen content the greater the organic porosity.

## **8. Summary and future work**

Since the 1970s, numerous geochemical studies have been conducted around the world, including improvements in analytical methods, the establishment of data interpretation guidelines, analogs for geochemical inversion and correlation, and improvements in fundamental understanding of petroleum generation, retention, expulsion, and migration. Application of geochemical characterization and interpretation plays a significant role in reducing risk in petroleum exploration. Nevertheless, many interpretation ambiguities and uncertainties still exist due to complex and unclear subsurface conditions. As advanced analytical data and greater volumes of data become available, integrating geochemistry, geology, data analytics, and modeling may help to further understand petroleum systems with fewer ambiguities and uncertainties. This integration will establish new concepts, workflows and improve estimates of unknown values in time and space.

## **Acknowledgements**

The authors wish to thank Chevron Corporation for permission to publish this work and thank Jessica Little and Michael Hsieh especially for performing Chevron's internal review before submission. We also would like to thank GeoMark for permission of using GC-MS traces in their database in this book chapter to show examples of different biomarker patterns in different types of oils.

*Petroleum Geochemistry DOI: http://dx.doi.org/10.5772/intechopen.104709*

## **Author details**

Mei Mei\* and Barry Katz Chevron Technical Center, a Division of Chevron U.S.A. Inc., USA

\*Address all correspondence to: meimei@chevron.com

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section 3
