Probabilistic Drilling Time Estimation Using Monte Carlo Simulation

Hyo-Jin Shin; Young-Il Choi; Yeong-Gyu Kim; Jong-Se Lim; Hyungbin Seo

doi:10.32390/ksmer.2018.55.3.205

All Issue

2018 Vol.55, Issue 3 Preview Page Next Page

Research Paper

Probabilistic Drilling Time Estimation Using Monte Carlo Simulation 몬테카를로 시뮬레이션을 이용한 확률론적 시추기간 예측

29 June 2018. pp. 205-212

PDF XML

Abstract

The economics of petroleum development project are highly dependent on the efficient drilling plan and implementation of drilling operation. Consequently, it is crucial to perform the drilling operation according to the plan. Uncertainties on reservoir conditions, drilling equipments and weather conditions should be considered for planning the drilling operation. In this study, Monte Carlo simulation was implemented with the consideration of the uncertainties in order to probabilistically estimate the drilling time using the field data. Main drilling operations were classified by analyzing the technical drilling data and they were used for base data for probabilistic drilling time estimation. The drilling time estimation technique using the probabilistic method will be utilized for future planning the drilling operations.

Keywords

Drilling time estimation

Monte Carlo simulation

Drilling data

Drilling operation

시추작업의 효율적 계획과 수행 여부에 따라 석유개발 사업의 경제성이 크게 좌우되며, 시간에 따른 시추공 굴착 깊이를 예측하여 시추작업을 수행하는 것이 중요하다. 시추작업은 저류층 상태, 시추장비, 날씨 등에 의한 불확실성이 있으며, 이를 고려한 시추계획 수립이 이루어져야 한다. 이 연구에서는 시추기간 예측 시 몬테카를로 시뮬레이션을 이용하여 불확실성을 고려한 확률론적 방법을 적용하고자 하였고, 현장 시추공 자료를 활용하여 시추기간 예측을 수행하였다. 이를 위해 시추 자료로 부터 주요 시추작업 항목을 분류하였으며, 확률론적 시추기간 예측을 위한 기초자료로 사용하였다. 확률론적 방법을 이용한 시추기간 예측 기술은 향후 시추계획 수립에 활용 가능할 것으로 사료된다.

키워드

시추기간 예측

몬테카를로 시뮬레이션

시추 자료

시추작업

References

Adams, A.J., Grundy, K.C., and Kelly, C.M., 2015. Probabilistic Well Time Estimation Revisited: Five Years On. Proc. of SPE/IADC Drilling Conference and Exhibition, London, England, UK, p.1-48.

10.2118/173028-MS

Akins, W.M., Abell, M.P., and Diggins, E.M., 2005. Enhancing Drilling Risk & Performance Management Through the Use of Probabilistic Time & Cost Estimating. Proc. of SPE/IADC Drilling Conference, Amsterdam, The Netherlands, p.1-9.

10.2118/92340-MS

Budzaya, U., 2013. A Study on Estimation of CBM Resources Using Probabilistic Approach from Coal Basin Information, Master Thesis, Chonnam National University, Gwangju, p.6-14.

Choi, S., Kim, J., Park, B., Bae, J., Jang, G., and Choi, J., 2011. Technical Review of the Drilling Operations of WA- 1001BX and Alm-1001BX in Block 4, Yemen. J. of Korean Society of Mineral and Energy Resources Engineers, 48(6), 802-812.

Chung, Y., 2013. Analysis and Evaluation of Net Present Value by means of Monte Carlo Simulation. J. of Korean Society of Hazard Mitigation, 13(6), 15-19.

10.9798/KOSHAM.2013.13.6.015

Hollund, K., Rosenlund, H., Akcora, S., and Hauge, R., 2010. Hitting Bull's-Eye with Time and Cost Estimates by Combining Statistics and Engineering. Proc. of SPE Annual Technical Conference and Exhibition, Florence, Italy, p.1-6.

Jang, G., Kang, B., Lim, J., Hwang, C., and Ryou, S., 1999. A New Approach to Reducing Drilling Costs in Offshore Drilling. J. of Korean Society of Mineral and Energy Resources Engineers, 36(6), 435-447.

Kim, J.S., Shin, H.J., and Lim, J.S., 2014. Probabilistic Decline Curve Analysis for Forecasting Estimated Ultimate Recovery in Shale Gas Play. J. of Korean Society of Mineral and Energy Resources Engineers, 51(6), 808-819.

Lim, J.S., Kang, P.S., and Kim, H.T., 2010. Current Technologies and Field Cases of Onshore Deep Oil Well Drilling. J. of Korean Society of Mineral and Energy Resources Engineers, 47(5), 809-821.

Merlo, A., Paolo, A., Tove, L., and Oystein, A., 2009. An Innovative Tool on a Probabilistic Approach related to the Well Construction Costs and Times Estimation. Proc. of EUROPEC/EAGE Conference and Exhibition, Amsterdam, The Netherlands, p.1-10.

10.2118/121837-MS

Min, T., Yi, J., Oh, H., Chun, Y., Bae, J., Jang, G., and Lee, S., 2012. Technical Review of the Drilling Operation of QT-1 in Block Qush tappa, Iraq. J. of Korean Society of Mineral and Energy Resources Engineers, 49(1), 80-90.

Radhwi, A.O., Amer, M.M., Idrees, H., Fakhruddin, A., and Hazzazi, M.A., 2013. WellPlanET_Smart & Efficient Drilling Well Program by Saudi Aramco. Proc. of SPE Middle East Intelligent Energy Conference and Exhibition, Manama, Bahrain, p.1-10.

10.2118/167481-MS

Saibi, M., 2007. A Probabilistic Approach for Drilling Cost Engineering and Management. Proc. of SPE/IADC Middle East Drilling and Technology Conference, Cairo, Egypt, p.1-13.

10.2118/107211-MS

Steve, D., 1998. Practical Well Planning and Drilling Manual, PennWell Books, Tulsa, Oklahoma, U.S.A., p.3-15.

Suh, J., Choi, Y., and Park, H., 2008. DrillerGeoDB: Windows- based Database Program for Effective Management of Drilling Data in Oil and Gas Industry. J. of Korean Society of Mineral and Energy Resources Engineers, 45(6), 707-718.

Williamson, H.S., Sawaryn, S.J. and Morrison, J.W., 2006. Monte Carlo Techniques Applied to Well Forecasting: Some Pitfalls. Proc. of SPE Annual Technical Conference and Exhibition, Houston, Texas, U.S.A., p.1-12.

Information

Publisher :The Korean Society of Mineral and Energy Resources Engineers
Publisher(Ko) :한국자원공학회
Journal Title :Journal of the Korean Society of Mineral and Energy Resources Engineers
Journal Title(Ko) :한국자원공학회지
Volume : 55
No :3
Pages :205-212
Received Date : 2018-06-15
Revised Date : 2018-06-26
Accepted Date : 2018-06-26
DOI :https://doi.org/10.32390/ksmer.2018.55.3.205

Journal of the Korean Society of Mineral and Energy Resources Engineers ISSN:2288-0291(Print) 2288-2790(Online) 한국자원공학회지

All Issue