Asnul Bahar

An Innovative Approach To Integrate Fracture, Well Test and Production Data into Reservoir Models

This paper presents an innovative approach to integrate fracture, well test and production data into the static description of a reservoir model as an input to the flow simulation. The approach has been successfully implemented into a field study of a giant naturally fractured carbonate reservoir in the Middle East. This study was part of a full field integrated reservoir characterization and flow simulation project. The main input available for this work includes matrix properties, fracture network, well test and production data. Stochastic models of matrix properties were generated using geostatistical methodology based on well logs, core, seismic data and geological interpretation. Fracture network was described in the reservoir as lineaments (fracture swarms) showing two major fracture trends. The network and its properties, i.e., fracture porosity and permeability, were generated by reconciling seismic, well logs, and dynamic data (well test and PLT). The challenge of the study is to integrate all the input in an efficient and practical way to produce a consistent model between static and dynamic data. As a result, it is expected to reduce the history matching effort. This challenge was solved by an innovative iterative procedure between the static and dynamic models. The static part consists of the calibration of model permeability to match the well test permeability. It is done by comparing their flow potentials, kh. In this analysis the dominant factor in controlling production at each well, either matrix or fracture, was determined. Based on the dominant factor, matrix or fracture permeability was modified accordingly. This way the changes in permeability are kept inline with the geological understanding of the field. The dynamic part was carried out through a full field flow simulation to integrate production data. The flow simulation at this stage was used to match production capacity, i.e. to determine whether the given permeability (matrix and fracture) distribution is enough to produce the fluid at the specified pressure during the producing period of the well. The iteration is stopped once a reasonable production capacity match is obtained. In general, a good match was achieved within 3-4 iterations. The generated reservoir description is expected to substantially reduce the effort required to obtain a good history match.

Integrated Reservoir Description and Flow Performance Evaluation: Glenn Pool Field — Self Unit Study

Abstract This paper presents the study of an integrated approach to reservoir description as a part of the DOE-Class I Projects to improve the oil recovery from a mature oil field. The field selected is the Self Unit of the Glenn Pool Field that covers 160 acres. An integrated reservoir description was constructed which honors the geological, geophysical, and engineering data using geostatistical (stochastic) as well as the deterministic models. The description was validated by comparing the simulated results with static (well log and well core) as well as dynamic (well test) information. Both stochastic and deterministic models replicate the geological model very well. The deterministic model predicts an optimistic performance, whereas the stochastic model follows the field data much better. The incorporation of geophysical information, taken from tomography surveys, improves the reservoir description when comparing with the observed well test information. Using the description from each of the models, the flow simulations were conducted to match the historical performance and to predict the future production. Based on the flow simulation and the economic analysis, the plan of recompleting the wells along with an increase in the injection rate is found to be the most feasible solution to improve the performance of the Self Unit. The preliminary results from the implementation of this plan indicate expected results.

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

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.

A Multi-Disciplinary Approach for Reservoir Characterization in the Glenn Pool Field, Oklahoma: Abstract

Abstract Glenn Pool, a mature marginal oil field, is located on the Northeastern Oklahoma Platform. It has been under production since the first discovery in 1905. Several reservoir treatments have been implemented in the last 50 years following the primary production. However, high reservoir complexity resulted in a large volume of oil to be left in place. Our research is focused on a 160-acre block (Self Unit) where a detailed multi-disciplinary (Geology, Geophysics, Petroleum Engineering) reservoir study was conducted. The purpose of the study is to improve the secondary recovery performance of the field through the use of proper reservoir description and better reservoir management. Prior to drilling a cooperative project well (Uplands Self #82) Self Unit was studied with conventional methods. Stratigraphic framework of the Glenn Sand reservoir has been established through a series of stratigraphic cross sections. Based on well log correlations the reservoir was divided into six discrete genetic intervals (DGI). Channel-fill, splay, channel-mouth bar, levee and interdistributary mudstone facies were recognized from well log profiles and core analysis. Attempts were made in simulating geology using simple kriging methods; results were not entirely satisfactory. Uplands Self #82 was drilled in late December, 1993. The project objectives for drilling the well were: 1) evaluate reservoir predictions; 2) collect data using conventional and advanced technologies. Facies architectural characterization before drilling was reasonably successful. Advanced technologies including microresistivity imaging log and crosswell tomography data were acquired as well as the conventional well log suites and core. Simulation of the DGI distribution was undertaken using truncated Gaussian simulation method. Simulation results strongly agree when comparing probability input distributions with the output distributions. Porosity distribution was simulated using the simulated annealing method, and permeability distribution was transformed from porosity using a conditional distribution approach. For a selected well location (Self #82) the comparison between simulated and core porosity/permeability is very good. Crosswell transmission and migrated reflection tomography images between Self #82 and three offset wells constrained lateral reservoir continuity. A reservoir management plan was developed from reservoir performance simulation, well test data, facies architecture and crosswell tomography.