**7. Conclusions**

The purpose of this chapter was to determine the mathematical expression that explains the possibility of a loss of position during DP drilling operations.

With a sample of 42 incidents from 2011 till 2015, it was determined that the mathematical expression for the binary logistic regression model is shown in Eq. 9. The loss of position of an incident depends on the water depth and the percentage of generators used.

With this model, it can be determined that the probability of loss of position will increase when the water-depth has small values and the percentage of generators has bigger values.

Having considered that the percentage of cases correctly classified by the model which takes into account both variables percentage of generators online and waterdepth is high (78.6%), it is expected to provide excellent results when predicting whether any incident will have a loss of position or not.

Once this model has been determined, the secondary objective of this paper was to find and compare the mathematical expression, taking into account whether the nature of the cause leading to the incident was human or not.

With a sample of 33 incidents without human cause, it was determined that the mathematical expression for determining the probability of loss of position is given in Eq. 13. This model can determine that the probability of having an excursion increases as the percentage of generators and the wind force have bigger values.

The percentage of cases correctly classified by the model according to this sample is high (75.8%), and it can be expected to provide excellent results when predicting whether an incident that has no human origin will have a loss of position or not.

The sample of the incidents with human cause was relatively small (9 cases only), so no independent variable could explain the model within a confidence interval of 10%. However, the variable water-depth, which appears above in the general model, and does not appear in the model for the cases without human cause, can be suspected to explain the model, although it will be necessary to perform further research on a bigger sample to obtain significant results.
