A Procedure to Integrate Well Test Data, Reservoir Performance History and 4-D Seismic Information into a Reservoir Description

Abstract

Abstract This paper deals with the problem of estimating the distributions of permeability and porosity in heterogeneous and multiphase petroleum reservoirs by matching the dynamic behavior. The dynamic data is in the form of field measurements from well testing, production history, interpreted 4-D seismic information, and other data such as correlations between permeability and porosity, geostatistics in the form of a variogram model and the inference of large scale geological structure. The issue was posed as an inverse problem and solved by using nonlinear parameter estimation. The procedure developed here is capable of processing all the information simultaneously and this results in a fast and efficient method. The procedure is also able to determine the uncertainty associated with the estimated permeability and porosity fields. Examples of different parameter types that may be estimated by this approach include:individual block permeabilities and porosities;geological objects such as channels and faults;pilot points that form the basis of a kriged distribution; andseismic attenuation values from 3-D seismic images. An important conclusion of this work is that the value of each piece of information does not reside in its isolated use but in the value it adds to integrated analysis of the complete set of information. Thus data that traditionally was considered to be of low information content for reservoir characterization becomes useful and enhances the value of the data set as a whole. Introduction Devising the optimal strategy for the development of an oil or gas reservoir is an important and difficult task. Many mathematical techniques for optimization can be used to deal with problems in engineering and economics systems. These techniques assume that we have a fairly complete understanding of the problem and also that we can construct a mathematical model that predicts the system's performance accurately in time under different scenarios; this is not a serious concern in most engineering problems since the parameters that define the system may not be very difficult to obtain by direct measurement. Unfortunately this is not the case in reservoir engineering, where the system, that is the oil-gas reservoir, is physically inaccessible many thousands of feet underground. Thus, any serious attempt at optimization of reservoir development first requires the determination of the parameters of the reservoir and the only way to obtain them is through indirect measurement. The process of inferring the parameters from the indirect measurements is an inverse or parameter estimation problem. Such is the focus of this work. Permeability and porosity are the parameters that have the largest influence in determining the performance of the reservoir, and thus, this work addresses the problem of estimating permeability and porosity from a variety of measurements that are only indirectly related to them. Estimating permeability and porosity is difficult for the following reasons:–Permeability and porosity have spatial variability–There are very few sampling locations (wells) compared to the areal extent of the reservoir.–Information (data) is scarce.–Measurements are obtained with different technologies.–The mathematical model of the reservoir is very complex, usually consisting of a numerical reservoir simulation. P. 99^