UNCERTAINTY ANALYSIS OF A GIANT OIL FIELD IN THE MIDDLE EAST USING SURROGATE RESERVOIR MODEL

Abstract

Uncertainty Analysis of a Giant Oil Field in the Middle East Using Surrogate Reservoir Model Shahab D. Mohaghegh; Shahab D. Mohaghegh West Virginia U. Search for other works by this author on: This Site Google Scholar Hafez H. Hafez; Hafez H. Hafez Abu Dhabi Co. Onshore Oil Opn. Search for other works by this author on: This Site Google Scholar Razi Gaskari; Razi Gaskari West Virginia U. Search for other works by this author on: This Site Google Scholar Masoud Haajizadeh; Masoud Haajizadeh Abu Dhabi Co. Onshore Oil Opn. Search for other works by this author on: This Site Google Scholar Maher Kenawy Maher Kenawy Abu Dhabi Co. Onshore Oil Opn. Search for other works by this author on: This Site Google Scholar Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, November 2006. Paper Number: SPE-101474-MS https://doi.org/10.2118/101474-MS Published: November 05 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Mohaghegh, Shahab D., Hafez, Hafez H., Gaskari, Razi, Haajizadeh, Masoud, and Maher Kenawy. "Uncertainty Analysis of a Giant Oil Field in the Middle East Using Surrogate Reservoir Model." Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, November 2006. doi: https://doi.org/10.2118/101474-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)Abu Dhabi International Petroleum Exhibition and Conference Search Advanced Search AbstractSimulation models are routinely used as a powerful tool for reservoir management. The underlying static models are the result of integrated efforts that usually includes the latest geophysical, geological and petrophysical measurements and interpretations. As such, these models carry an inherent degree of uncertainty. Typical uncertainty analysis techniques require many realizations and runs of the reservoir simulation model. In this day and age, as reservoir models are getting larger and more complicated, making hundreds or sometimes thousands of simulation runs can put considerable strain on the resources of an asset team, and most of the times are simply impractical. Analysis of these uncertainties and their effects on well performance using a new and efficient technique is the subject of this paper. The analysis has been performed on a giant oil field in the Middle East using a surrogate reservoir model.The surrogate reservoir model that runs and provides results in real-time is developed to mimic the capabilities of a full field simulation model that includes one million grid blocks and takes 10 hours to run using a cluster of twelve 3.2 GHz CPUs. In order to effectively demonstrate the robustness of Surrogate Reservoir Models and their capabilities as tools that can be used for uncertainty analysis, one must demonstrate that SRMs are competent in providing reasonably accurate results for multiple realizations of the reservoir being studied. In order to demonstrate such robustness and their predictive capabilities as well as their limitations, this paper will examine the performance of the surrogate reservoir models on different geologic realizations of the static model.IntroductionIn two previous SPE papers some of the aspects of the Surrogate Reservoir Models were discussed. In the first paper1 the idea of Surrogate Reservoir Models was introduced and in the second paper2 its application in quantifying uncertainties associated with a reservoir simulation study was explored. Keywords: Modeling & Simulation, Upstream Oil & Gas, risk management, risk assessment, spe 101474, simulation model, reservoir simulation, blind well, simulation run, realization Subjects: Reservoir Simulation, Risk Management and Decision-Making, Risk, uncertainty, and risk assessment This content is only available via PDF. 2006. Society of Petroleum Engineers You can access this article if you purchase or spend a download.