Abstract: Improved Reservoir Modeling through Data Integration: Geostatistical Application Examples

William M. Bashore, Udo G. Araktingi

As the economic climate within the oil and gas industry increasingly demands better exploitation of currently producing fields, a corresponding demand is placed on reservoir geoscientists and engineers to better describe and quantify the nature of the producing reservoirs. This implies that the diverse information supplied by the numerous disciplines involved with data collection and analysis must be integrated to generate improved reservoir models. One particularly well-suited tool for multiple dataset integration that is gained in widespread interest and usage is the field of spatial statistics. This paper presents results from case studies demonstrating the application of various geostatistical techniques.

The selected ensemble of carbonate and siliciclastic examples highlight several key points. First, geologic interpretations provide the foundation upon which any geostatistical application must be based. For instance, core measurements relating porosity and permeability must be segregated and statistically handled within the appropriate facies context. Additionally, the spatial estimations of reservoir parameters from well to well should reflect local depositional and diagenetic factors. Incorporating the proper geologic framework implies that reservoir geologists must be intimately involved with the creation of numerical models for engineering and decision making purposes. The second point is that the integration of seismically-derived acoustic measurements from 2D, 3D, and crosswell reflection surveys with well and core data can substantially improve interwell predictions of reservoirs heterogeneities. Comparisons of flow simulation results from models with and without the seismic data integrated for both field and synthetic studies are given.

AAPG Search and Discovery Article #90986©1994 AAPG Annual Convention, Denver, Colorado, June 12-15, 1994