A new quantitative evaluation method for drilling risk based on uncertainty analysis

Authors

  • Zhichuan Guan China University of Petroleum
  • Ya-Nan Sheng
  • Ming Luo
  • Yuqiang Xu
  • Bo Zhang
  • Qing Wang

Keywords:

Drilling risk evaluation, Formation pressure with credibility, ECD with credibility, Monte Carlo simulation, Generalized stress and strength interference theory

Abstract

With drilling operations extending to offshore or deep and complex formations, drilling risk is becoming more and more serious. Traditional methods cannot assure the safety of high-risk drilling operations. Therefore, establishing a quantitative evaluation method for drilling risk is becoming increasingly more urgent. In this paper, the credibility of formation pressure
and equivalent circulation density (ECD) of drilling fluid were first analyzed based on the Monte Carlo simulation method. Thereafter, the probability distributions of formation pressure and ECD were obtained. Then, based on the generalized stress and strength interference theory, the quantitative method for evaluating drilling risk was established. In this method, the risk
factor was defined as the generalized stress (ECD). The safety factor was defined as the generalized intensity (formation pressure). The safety barrier function was defined as the function of drilling risk. In two case studies, this method was used to predict drilling risk probabilities, and the prediction results were in favorable agreement with the actual drilling risk.

References

Ahmed, U., Bordelon, D. & Allen, D. (1993). MWD

rock mechanical properties to avoid drilling related

problems. Proceedings of the SPE/IADC Drilling

Conference. Society of Petroleum Engineers. Amsterdam,

Netherlands.

Austin, E.H. (1983). Drilling engineering handbook.

International Human Resources Development Corp.,

Michigan, USA. pp. 62- 75.

Bratton, T., Edwards, S., Fuller, J., Murphy, L.,

Goraya, S., Harrold, T. …Wright, B. (2001). Avoiding

drilling problems. Oilfield Review, 13(2): 22- 30.

Gandelman, R. A., Martins, A.L., Teixeire, G.T.,

Waldmann, A.T., Rezende, M.S. & Aragoa, F.L. (2009).

A comprehensive methodology to avoid and remediate

drilling problems by real-Time PWD data interpretation.

Proceedings of the SPE Annual Technical Conference and

Exhibition. New Orleans, LA, USA. Society of Petroleum

Engineers.

Hempkins, W.B., Kinsborough, R.H., Lohec, W.E. &

Nini, C.J. (1987). European Patent Office. EP0209343.

Munich, Germany: European Patent Office.

Higgins, J. G. (1993). Planning for risk and uncertainty

in oil exploration. Long Range Planning, 26(1): 111122-.

Hirsch, W.M., Meisner, M. & Boll, C. (1968).

Cannibalization in multicomponent systems and the

theory of reliability. Naval Research Logistics Quarterly,

(3): 331–360.

Huang, Z. & Jin, Y. (2009). Extension of stress and

strength interference theory for conceptual design for

reliability. Journal of Mechanical Design, 131(7): 111-.

Irani, R. & Nasimi, R. (2011). Application of artificial

bee colony-based neural network in bottom hole pressure

prediction in underbalanced drilling. Journal of Petroleum

Science & Engineering, 78(1): 6- 12.

Ke, Z., Guan, Z.C. & Zhou, X. (2009). An approach

to determining pre-drilling formation pore pressure with

credibility for deep water exploration wells. Journal of

China University of Petroleum, 33(5): 61 -67.

Khakzad, N., Khan, F. & Amyotte, P. (2013).

Quantitative risk analysis of offshore drilling operations:

A Bayesian approach. Safety Science, 57(57): 108 -117.

Lerche, I. (2012). Geological risk and uncertainty in oil

exploration. Academic Press, San Diego, USA. pp.44 -52.

Liu, J., Li, Q. & Wang Y. (2013). Risk analysis in

ultra-deep scientific drilling project—A fuzzy synthetic

evaluation approach. International Journal of Project

Management, 31(3): 449 -458.

Mokhtari, M., Ermilla, M.A., Tutuncu, A. N. &

Karimi, M. (2012). Computational modelling of drilling

fluids dynamics in casing drilling. Proceedings of the SPE

Eastern Regional Meeting. Lexington, KY, USA. Society

of Petroleum Engineers.

Mostafavi, V., Aadnoy, B.S. & Hareland, G. (2011).

Model-Based uncertainty assessment of wellbore stability

analyses and down-hole pressure estimations. Proceedings

of the 45th U.S. Rock Mechanics/ Geomechanics

Symposium. San Francisco, CA, USA. American Rock

Mechanics Association.

Peng, Q., Fan, H., Zhou, H., Li, C., Chen, X., Wang,

E. & Ye, Z. (2013). General method of calculating

annular laminar pressure drop of drilling fluids with

different rheological models. Petroleum Exploration and

Development, 40(6): 806 -810.

Reitsma, Donald G. (2009). Method for determining

formation fluid entry into or drilling fluid loss from a

borehole using a dynamic annular pressure control system.

United States Patent Office. US7562723. Alexandria,

Virginia, USA: United States Patent Office.

Sadiq, R., Husain, T., Veitch, B. & Bose, N. (2004).

Risk-based decision-making for drilling waste discharges

using a fuzzy synthetic evaluation technique. Ocean

Engineering, 31(16): 1929- 1953.

Sheng, Y.N., Guan Z.C. & Zhao, T. (2016). Study on

method of determining the formation pressure with

credibility. Science Technology and Engineering, 16(2):

-42.

Skogdalen, J.E. & Vinnem J.E. (2012). Quantitative risk

analysis of oil and gas drilling, using Deepwater Horizon

as case study. Reliability Engineering and System Safety,

(10): 58 -66.

Subramanian, R. & Azar, J.J. (2000). Experimental

study on friction pressure drop for Non-Newtonian

drilling fluids in pipe and annular flow. Proceedings of

the International Oil and Gas Conference and Exhibition.

Beijing, China. Society of Petroleum Engineers.

Sundararajan, C. & Witt, F.J. (1995). Stress-strength

inference method. In: Sundararajan, C., Eds Probabilistic

Structural Mechanics Handbook. Springer, Boston, MA,

USA. pp. 85- 91.

Von Eberstein, W.H., Mayo, G.H., Weaver, M.A.,

van Oort, E. & Kotara Jr., E.B. (2004). Method for

formation pressure control while drilling. United States

Patent Office. US6823950 B2. Alexandria, VA, USA:

United States Patent Office.

Warren M. Hirsch †, Meisner M, Boll C. (1968).

Cannibalization in multicomponent systems and the theory

of reliability[J]. Naval Research Logistics Quarterly,

(3):331–360.

Wessling, S., Bartetzko, A. & Tesch. P. (2014). Method to

predict overpressure uncertainty from normal compaction

trendline uncertainty. United States Patent Office. US

A1. Alexandria, VA: United States Patent

Office.

Downloads

Published

28-08-2018

Issue

Section

Earth & Environment