Trends in Reservoir Simulation: Big Models, Scalable Models? Will you Please Make up Your Mind? (2001)

Trends in Reservoir Simulation: Big Models, Scalable Models? Will you Please Make up Your Mind? Sheldon Gorell; Sheldon Gorell Landmark Graphics Corporation Search for other works by this author on: This Site Google Scholar Robert Bassett Robert Bassett 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, New Orleans, Louisiana, September 2001. Paper Number: SPE-71596-MS https://doi.org/10.2118/71596-MS Published: September 30 2001 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Gorell, Sheldon, and Robert Bassett. "Trends in Reservoir Simulation: Big Models, Scalable Models? Will you Please Make up Your Mind?." Paper presented at the SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, September 2001. doi: https://doi.org/10.2118/71596-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Annual Technical Conference and Exhibition Search Advanced Search AbstractOver the past 20–30 years, reservoir simulation technology has gone through various stages of acceptance and utilization. This paper will discuss the most common workflows as well as several of the emerging trends in reservoir simulation technology, particularly:building ever larger increasingly complex simulation models,building smaller models, which can be evaluated quickly, andbuilding scalable or "fit for purpose" models. This paper will discuss these trends in more detail, reconcile these approaches and discuss the appropriateness of each method. Potential conflicts with respect to the user profile and the differing demands imposed on development and usage of a reservoir simulation system will also be discussed relative to each of these workflows.IntroductionReservoir simulation technology is currently approaching a point where it is considered mature and reservoir simulation has become almost universally accepted as a reservoir management tool. This is evidenced by the fact that many companies now require reservoir simulation studies prior to initiating new field developments or modifying a field development strategy.Although software tools for creation of simulation models, the simulators themselves and simulation analysis tools have improved, most of the concepts and the fundamental workflows have remained largely unchanged since their inception. There are a few variations of the "Traditional" workflow, but they usually involve many of the following steps:Collect and gather all the relevant reservoir data,Perform quality assurance on the data and rationalize any inconsistencies,Build a model, or possibly a few models,Run simulations, including sensitivities,If history matching then make changes to the model to match the past performance, andPerform prediction cases.From the perspective of this paper, these traditional workflows will also be referred to as "Deterministic" workflows. Although all reservoir simulation calculations are deterministic in nature, this term is used because it provides a frame of reference to contrast other non-traditional workflows, which are less deterministic in the outcomes they produce.Recently, some variations of the "tried and true" traditional deterministic workflows have started to develop. These focus on building smaller simulation models, which can be evaluated quickly. The motivation for creating and running smaller models has been driven by the desire to quantify and manage uncertainty and risk. Instead of running a few very detailed simulations, the goal is to run many calculations, where key parameters are chosen to span the uncertainties that may affect reservoir recovery. As a contrast to the traditional workflows, these will be referred to as "Probabilistic" workflows. This term is used to characterize these workflows because the results are ranges or distributions of outcomes. Keywords: gridblock, reservoir characterization, requirement, usability, calculation, sensitivity, simulation, reservoir simulation, upstream oil & gas, geologic modeling Subjects: Reservoir Characterization, Reservoir Simulation, Geologic modeling This content is only available via PDF. 2001. Society of Petroleum Engineers You can access this article if you purchase or spend a download.