Addressing the Challenges of Production Forecasting in the Remote Highlands of Papua New Guinea
- Stephanie Sullivan (Oil Search Limited) | Jon Rowse (Oil Search Limited)
- Document ID
- Society of Petroleum Engineers
- SPE Economics & Management
- Publication Date
- September 2013
- Document Type
- Journal Paper
- 15 - 20
- 2013. Society of Petroleum Engineers
- 7.3.3 Project Management, 5.6.9 Production Forecasting
- 2 in the last 30 days
- 287 since 2007
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Operational conditions in the remote highlands of Papua New Guinea (PNG)bring a multitude of challenges, including complex geology, steep jungleterrain, extreme rainfall, a sensitive ecosystem, a variety of landownercultures, ageing facilities, mature reservoirs, and fraught logistics. Thesefactors conspire to increase the complexity of production forecasting wellbeyond just reservoir performance. After missing production targets for anumber of years, a significant improvement in forecasting was needed to fullycapture the uncertainties, both identified and unforeseen. A probabilisticforecasting tool by use of Monte Carlo simulation has been developed, whichincorporates assessments of all major variables and takes account of historicalperformance and system changes. Successful implementation has resulted in thegeneration of realistic targets that have been met within 4% for 4 years.Further, a clearer understanding of potential threats and opportunities,combined with their impact on production, has been achieved. These results havedelivered material benefits to business planning, decision making, and companyreputation. Data to be presented on the forecasting tool will describe thequantification of uncertainty for each major variable, including reservoir andfacility performance, incremental production opportunities, project schedules,and major unplanned downtime. This approach could be applicable to explorationand production companies operating in difficult conditions worldwide, in areaswhere unreliable production targets have a major business impact. It isflexible enough for both short- and long-term forecasts, tracking andreporting, and adaptation to new or changed operating conditions.
|File Size||975 KB||Number of Pages||6|
Adepoju, O., Olufemi, O. and Djuro, N. 2009. Improving Production Forecaststhrough the Application of Design Experiments and Probabilistic Analysis: ACase Study from Chevron, Nigeria. Paper SPE 128605 presented at Nigeria AnnualInternational Conference and Exhibition, Abuja, Nigeria, 3-5 August. http://dx.doi.org/10.2118/128605-MS.
Bickel, J. and Bratvold, R. 2007. Decision Making in the Oil and GasIndustry: From Blissful Ignorance to Uncertainty-Induced Confusion. Paper SPE109610 presented at the SPE Annual Technical Conference and Exhibition,Anaheim, California, 11-14 November. http://dx.doi.org/10.2118/109610-MS.
Can, B. and Kabir, C.S. 2011. Probabilistic Performance Forecasting forUnconventional Reservoirs with Stretched-Exponential Model. Paper 143666presented at the SPE North American Unconventional Gas Conference andExhibition, The Woodlands, Texas, 14-16 June. http://dx.doi.org/10.2118/143666-MS.
Cheng, Y., Wang, Y., McVay, D.A., et al. 2005. Practical Application of aProbabilistic Approach to Estimate Reserves Using Production Decline Data.Paper SPE 95974 presented at the SPE Annual Technical Conference andExhibition, Dallas, Texas, 9-12 October. http://dx.doi.org/10.2118/95974-MS.
Jonkman, R.M., Bos, C.F.M., Breunese, J.N., et al. 2000. Best Practices andMethods in Hydrocarbon Resource Estimation, Production and EmissionsForecasting, Uncertainty Evaluation and Decision Making. Paper SPE 65144presented at the SPE European Petroleum Conference, Paris, France, 24-25October. http://dx.doi.org/10.2118/65144-MS.
Peterson, S.K., De Wardt, J. and Murtha, J.A. 2005. Risk and UncertaintyManagement - Best Practices and Misapplications for Cost and ScheduleEstimates. Paper SPE 97269 presented at the SPE Annual Technical Conference andExhibition, Dallas, Texas, 9-12 October 2005. http://dx.doi.org/10.2118/97269-MS.
Rose, P.R. 2004. Delivering On Our E&P Promises. The Leading Edge 23 (2): 165-168. http://dx.doi.org/10.1190/1.1651465.
Ross Carmichael Singer. 2012. Corporate Confidence Index. Independent reportprepared annually for Oil Search Limited to benchmark institutional investorsentiment. Independent report, Chatswood, New South Wales, Australia(unpublished).
Spencer, J. A. and Morgan, D. T. K. 1998. Application of Forecasting andUncertainty Methods to Production. Paper SPE 49092 presented at the SPE AnnualTechnical Conference and Exhibition, New Orleans, Louisiana, 27-30 September.http://dx.doi.org/10.2118/49092-MS.
Williamson, H.S., Sawaryn, S.J. and Morrison, J.W. 2006. Monte CarloTechniques Applied to Well Forecasting: Some Pitfalls. SPE Drill &Compl 21 (3): 216-227. http://dx.doi.org/10.2118/89984-PA.
Wolff, M. 2010. Probabilistic Subsurface Forecasting-What Do We Really Know?J. Pet. Tech. 62 (5): 86-92. http://dx.doi.org/10.2118/118550-MS.