Fully Integrated 3D-Reservoir Characterization and Flow Simulation Study: A Field Case Example

Autor: Asnul Bahar, Tono Soeriawinata, Harun Ates, Salem El-Abd, Maged H. Al-Deeb, Mohsen Charfeddine, Gerard Bloch, Mohan Kelkar
Rok vydání: 2002
Předmět:
Zdroj: All Days.
DOI: 10.2118/78510-ms
Popis: This paper was selected for presentation by an SPE Program Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, SPE, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972- 952-9435. Abstract This paper presents the result of fully 3D integrated reservoir description and flow simulation study of a giant oil field in Middle East using the state of the art technology. The overall goal is to develop a representative reservoir model to form the basis for reservoir management and long- term development planning. This is done by generating alternate reservoir descriptions, based on stochastic models, to quantify uncertainties in the future performance. The data that were integrated include well cores and logs, geological interpretation (stratigraphy, rock type, depositional model), seismic (structure, curvature analysis and inversion-derived porosity), well test, SCAL, production data and fracture distribution. The 3D multiple realizations were generated by considering rock type and petrophysical properties at well location, obtained from well logs and cores, and simultaneously constrained by seismic derived porosity. The simulations of properties were generated using simultaneous sequential Gaussian simulation where the seismic constraint was introduced via Bayesian Updating procedure. Special consideration was given to the spatial modeling of data where soft information was derived both from hard data and depositional environment. Fracture distribution, derived from seismic curvature analysis, was used in the integration process to match the core-based derived permeability with well test permeability. This distribution was used to obtain permeability anisotropy distribution using newly developed tensorial approach. A total of forty-eight realizations were generated considering four major types of uncertainties: structure, spatial model, petrophysical properties and simulation path. The results have been used as the basis for fluid in place (STOIIP) calculation using Monte Carlo simulation technique. These realizations are then ranked based on the sweep efficiency, obtained from multiphase streamline simulations, and the STOIIP. Three realizations, representing medium, low and high realizations, were selected and upscaled. An optimum vertical upscaling level was determined using streamline simulator and developing quantitative criterion. This ensures that the representative heterogeneity of the reservoir was maintained during the upscaling process. Comprehensive history matching was done for the three selected realizations for the entire nineteen years of production history using objective criterion so that the quality of the three matches is similar. The observed data matched include water cuts and measured pressures. The parameters used to match the history are restricted to the parameters that have not been accounted for in the static model. Using probabilistic concepts, uncertainties in future performance were quantified for various scenarios.
Databáze: OpenAIRE