The Construction And Application of Stochastic Models in Early Evaluation Phase of Oil Reservoirs

Abstract

Abstract In recent years, stochastic modeling technique has become a hot topic in reservoir characterization. Wherease, what should be made clear, if the technique is used in constructing geological models in early evaluation phase, is what problems in oil-gas development study can be solved by this technique. In this paper, focusing on the early evaluation phase of reservoir, the application cases from two reservoirs are used to discuss what practical problems can be solved by sectional reservoir models, which were built up by means of this technique. Introduction The development of oil-gas field is such a repeated process that is from practice to knowledge, and then to practice again. During the process the development of oil-gas field goes in phases because the information available and the destination to be reached at different stages would differ greatly. The early evaluation phase of reservoir is referred here to the period that begins from the discovering of an oil-gas field till the decision makIng of development. The goals of reservoir geology in early evaluation phase are l)to determine reservoir area, 2)to prove reserves, and 3) to asses reservoir properties and to work on the studies of development feasibility. So one of the purposes of reservoir modeling in early evaluation phase is to provide a proper conceptual reservoir model as an important input for numerical reservoir simulators. The problems of early evaluation phase is the lack of information available. Generally, the information available in this phase is that of exploration wells and evaluation wells, which are far spaced >1km), and some seismic data. At this circumstance, the deterministic models, derived from applying now day's technique in describing or estimating the reservoir attributes between wells, frequently can not satisfy certain demand of numerical reservoir simulators. Stochastic reservoir modeling techniques, aiming at characterizing the spatial heterogeneity of reservoir (petrophysical property) to satisfy the need of numerical reservoir simulators, can improve deterministic modeling techniques in some aspects and have become increasingly popular in recent years. Whereas, how many problems can be solved by it must be made clear before applying it in constructing reservoir models. The basic theory of stochastic simulation includes two aspects;generating a series of stochastic realizations according to the univariate and/or bivariate function derived from the statistic of experimental sample data; the univariate and bivariate parameters of simulated realizations are the same as those of the experiment sample data, which is called unconditional simulation;only reserving those in which the sample data is honored at sampling locations, which is called conditional simulation. P. 175