Decision Making With Uncertainty While Developing Multiple Gas/Condensate Reservoirs (2005)

Decision Making With Uncertainty While Developing Multiple Gas/Condensate Reservoirs C. Shah Kabir; C. Shah Kabir Chevron Corp. Search for other works by this author on: This Site Google Scholar Sheldon Burt Gorell; Sheldon Burt Gorell Landmark Graphics Corporation Search for other works by this author on: This Site Google Scholar Maria Portillo; Maria Portillo Chevron North America E&P Search for other works by this author on: This Site Google Scholar A. Stan Cullick A. Stan Cullick Landmark Graphics Corporation Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas, October 2005. Paper Number: SPE-95528-MS https://doi.org/10.2118/95528-MS Published: October 09 2005 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Kabir, C. Shah, Gorell, Sheldon Burt, Portillo, Maria, and A. Stan Cullick. "Decision Making With Uncertainty While Developing Multiple Gas/Condensate Reservoirs." Paper presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas, October 2005. doi: https://doi.org/10.2118/95528-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Annual Technical Conference and Exhibition Search Advanced Search AbstractWell-developed methodology exists for handling uncertainty for a single reservoir. However, development of multiple fields presents significant challenge when uncertainty in large number of variables, such as gas-in place and liquid yield, occur in each reservoir. Some of the challenges stem from our need to forecast the system behavior involving a coupled reservoir/wellbore/surface (CRWS) network for the entire spectrum of variables so that facilities can be designed for the range of fluid composition and throughput. Of course, assessing well count and sequencing well drills are some of the important objectives.This paper describes probabilistic production forecasting with a compositional CRWS network model for nine reservoirs involved in delivering gas supply to a LNG plant in Nigeria. Our main objective was to use an economic indicator to select optimal design of two main pipelines, each transporting 200 and 300 MMscf/D from the two production platforms, located 15- and 5-km, respectively, from the processing platform.Rate and cumulative profiles showed that sustained deliverability of gas can be realized for about 11 years before the decline occurred in high-permeability reservoirs. In other words, uncertainty in gas-in-place did not surface during the plateau period, only during the decline period lasting another five years, after the first eleven. In contrast, the liquid rates exhibited large uncertainty band throughout, a direct manifestation of the condensate yield issue. The uncertainty band among each of the 12 components aided facilities design. Differences in net present value (NPV) and discounted profitability index (DPI) were used as discriminators for discerning optimal pipe size from the standpoint of project economics.IntroductionIn recent years, probabilistic forecasting has gained popularity and has become the preferred approach when assessing the value of a project, given the uncertainty of many input variables. Uncertainties arise because both static and dynamic variables are ascertained from rather small volumetric samples of a reservoir and subsequent key variables are estimated from interpretations. Systematic approaches have emerged to account for uncertainty of both static and dynamic variables involving statistical approaches. These methods have been detailed elsewhere for a single reservoir.1–3 However, very few studies exist when production is sought from multiple reservoirs with uncertainty associated with each one of them.Cullick,4 Narayanan et al.,5 and Cullick et al.6 have presentedcase studies of production forecasting under uncertainty for multiple fields. In their studies, simulation tools were integrated with economic evaluation tools and Monte Carlo algorithm. Optimization was sought for an objective function (NPV, for instance) honoring various constraints.The objective of this study was to investigate the impact of uncertainty in input variables on the production forecast for systems consisting of multiple gas/condensate reservoirs, honoring wellbore constraints. We studied multiple reservoirs with multiple wells producing independently. The complexity arises because of the interactions through the common flowline system. The wellbore model was coupled with the reservoir model to honor wellbore constraints. The surface network interfaced with disparate wells through producing rules or constraints. In this study, the types of uncertainty considered are in-place volume, condensate yield, capital costs, and operating costs.We segmented this study into two phases. In phase 1, we developed an analytic simulator to generate the pressure and production forecasts for dry-gas reservoirs, coupled with a simple economic model but without the surface network. The intrinsic idea was to establish well count with a simplistic approach on a spreadsheet. In phase 2, a CRWS model allowed us to discern pipe diameter of two main trunk lines, transporting gas/condensate fluids, using incremental economics. Keywords: constraint, network model, upstream oil & gas, reservoir, depth surface, iteration, artificial intelligence, gas production, complex reservoir, reservoir surveillance Subjects: Well & Reservoir Surveillance and Monitoring, Reservoir Simulation, Unconventional and Complex Reservoirs, Gas-condensate reservoirs This content is only available via PDF. 2005. Society of Petroleum Engineers You can access this article if you purchase or spend a download.