Calculating the Optimal Time of Fishing Operations During Drilling in the Gachsaran Oil Field

Shadizadeh, Seyed Reza; Khajehniyazi, Sina

doi:10.22050/ijogst.2023.418574.1696

Calculating the Optimal Time of Fishing Operations During Drilling in the Gachsaran Oil Field

Document Type : Research Paper

Authors

Seyed Reza Shadizadeh ¹

Sina Khajehniyazi ²

¹ Professor, Department of Petroleum Engineering, Abadan Faculty of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran

² M.S. Student, Department of Petroleum Engineering, Ahwaz Faculty of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran

https://doi.org/10.22050/ijogst.2023.418574.1696

Abstract

Fishing operations are one of the most essential parts of drilling operations. If the fishing operation fails, the other direction should be considered to continue drilling and reach the desired depth, which can be achieved using sidetracking operations. Long-term fishing operations increase the cost and time of the drilling operation; therefore, we should try to have a successful fishing operation in the shortest possible time. It can be stated that the execution of the fishing operation is economical as long as the costs are less or at least equal to the cost of the sidetracking operation. Therefore, the optimal fishing time must be determined to make the drilling operation economical. Many statistical analysis methods have been used to determine the optimal time, but they are not popular due to insufficient accuracy and time-consuming calculations. This study used a machine-learning (ML) model with a regression algorithm to estimate the optimal time for fishing operations in the Gachsaran oil field. The fishing cost rate and depth as input data were first collected and categorized based on different sections of the Gachsaran oil field to calculate the optimal fishing time. Then, the sidetracking cost was predicted by the machine learning model, and this cost was equated to the fishing cost in the worst conditions. As a result, the optimal fishing time was calculated for each section. The result showed that the model could estimate the cost of sidetracking with an error of less than 2%. Using the designed model and the input data of the Gachsaran oil field, considering the optimal fishing time, it was possible to save $1 million and 16 h in drilling a well.

Highlights

Investigating fishing and sidetracking operations in the Gachsaran oil field;
Using the collected data in a machine-learning model to calculate the cost of sidetracking;
Analyzing formulas for calculating the cost of fishing and sidetracking to estimate the cost of fishing;

Keywords

Fishing

Sidetracking

Gachsaran Oil Field

Machine Learning

Optimum Time

Subjects

Petroleum Engineering – Drilling

Abbas, A. K., Flori, R., Almubarak, H., Dawood, J., Abbas, H., Alsaedi, A., Intelligent prediction of stuck pipe remediation using machine learning algorithms, SPE Paper No.196229 MS, SPE Annual Technical Conference and Exhibition, Canada, Calgary, Alberta, 30 September 2019.

Adams, N. and Charrier, T., Drilling engineering: a complete well planning approach, PennWell Publication, USA, Okla, Tulsa, p.849, 1985.

Adkins, C., Economics of Fishing, Journal of Petroleum Technology, Vol. 45, No. 05, p. 402–404, 1993.

Ahmadian Loraki, A. and Baneshi, M., Predicting the duration of Fishing with the help of artificial neural networks, Scientific- Propagative Journal of Oil & Gas Exploration & Production, Vol. 93, No. 17, p. 79–82, 2012.

Almeida, A. L., Silva, I. M., and Ramos, J. S., A Fishing operations expert system, SPE Paper No. 37590 MS, SPE/IADC drilling conference, Amsterdam, Netherlands, 4–6 March 1997.

Goodfellow, I., Bengio, Y., and Courville, A., Deep learning, MIT Press Publication, USA, Massachusetts, Cambridge, p.800, 2016.

Harrison, C. G., Fishing Decisions Under Uncertainty, Journal of Petroleum Technology, Vol. 34, No. 02, p. 299–300, 1982.

Keller, P., Brinkmann, P., and Taneja, P., Economic and statistical analysis of time limitations for spotting fluids and fishing operations, SPE Paper No. 4792 MS, Offshore Technology Conference, USA, Texas, Houston, 07 May 1984.

Khajehniyazi, S. Estimation of Optimum Fishing Time During Drilling Operation Using Artificial Intelligent Network: Gachsaran Oil Field. MS Thesis, Petroleum University of Technology, Iran, Ahwaz 2022.

Liang, P. and Bose, N., Neural network fundamentals with graphs, algorithms, and applications, Mac Graw-Hill Science Press, USA, New York, p.478, 1996.

Mani, G., Chen, F., Cross, S., Kalil, T., Gopalakrishnan, V., Rossi, F., and Stanley, K., Artificial intelligence’s grand challenges: past, present, and future, AI Magazine, Vol. 42, No. 1, p. 61–75, 2021.

Mohanna, A., Voghell, M., Alali, A., Bakir, R., and Al-Mousa, A., A step change in fishing efficiency: Recovering stuck pipe using the Fishing Agitation Tool, SPE Paper No. 160880 MS, SPE Saudi Arabia Section Technical Symposium and Exhibition Conference, Saudi Arabia, Al-Khobar, 08 April 2012.

Mullainathan, S. and Spiess, J., Machine learning: an applied econometric approach, Journal of Economic Perspectives, Vol. 31, No. 2, p. 87–106, 2017.

NISOC, D. E., Gachsaran Oil Field Final Drilling Reports, Iran, Ahwaz, p. 346, 2011.

Safari, M., Calculation of optimal fishing time, Scientific- Propagative Journal of Oil & Gas Exploration & Production, Vol. 5, No. 8, p. 14–15, 2003.

Sharma, N., McDonald, M., Mohammed, J., Daire, B., Eicks, T., and Jew, L., Optimizing directional drilling while minimizing the risk of well collision in offshore drilling, SPE Paper No. 124246 MS, SPE Annual Technical Conference and Exhibition? USA, Louisiana, New Orleans, 04 October, 2009.

Slinker, B. K. and Glantz, S. A., Multiple linear regression: accounting for multiple simultaneous determinants of a continuous dependent variable, Journal of Circulation, Vol. 117, No. 13, p. 1732–1737, 2008.

Torne, J., Rourke, M., Derouen, B., and Kessler, C., Middle East Case-Study Review of a New Free-Pipe Log for Stuck-Pipe Determination and Pipe-Recovery Techniques, SPE Paper No. 147859 MS, SPE Asia Pacific Oil and Gas Conference and Exhibition, Indonesia, Jakarta, 20 September, 2011.