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Abstract

The application of an Artificial Intelligence (AI) technique to assist in the selection of an Enhanced Oil Recovery process (EOR) is described. The aim of this Expert System (ES) is to provide reasoned comments on the applicability of such processes on the basis of reservoir characteristics. The knowledge base has been developed using a professional inference engine. To be closer to the type of reasoning used by experts, fuzzy logic concepts have been introduced in the knowledge representation.

This approach leads to a methodology for selecting EOR processes and for improving know-how by checking the criteria used by comparison with practical experience, and it helps to transfer the expert's knowledge to the users of the system. Moreover, estimations of additional field cases makes it possible to continuously refine the screening procedure.

Introduction

Expert systems (ES) are sophisticated computer programs that manipulate knowledge to solve problems efficiently and effectively in a narrow problem area. Like real human experts, these systems use symbolic logic and heuristics/rules-of-thumb to find solutions. This kind of software, also called Knowledge-Based System (KBS), today constitutes the most operational aspect of AI methods.

Various problems occurring in production are solved using a KBS approach. This article discusses the construction of an advisor system for selecting possible EOR processes in account of reservoir characteristics.

First, the diagnosis problem is defined and some of its difficulties are stressed. The type of reasoning is illustrated by the example of carbon dioxide (CO2) flooding.

Then, the architecture of the system is described, and the method for formalizing the knowledge is indicated using fuzzy logic concepts.

THE DIAGNOSIS PROBLEM

EOR methods or processes have as their objectives to increase recovery from reservoirs which would not respond to conventional waterflooding or gas injection.

The choice of enhanced recovery processes is based on technical and economic criteria. The problem involved is to find all the EOR processes applicable to the oil field concerned, or to check the suitability of a particular process in the light of the information available about the reservoir. in this application, we considered only the technical criteria of process application, since economic criteria are too subject to change from one company to another, but they could be easily added taking into account each petroleum company strategy.

Another very important aspect in the choice of a process is the possibility of obtaining precise documentation on reservoirs similar to the reservoir studied.

Why an Expert System?

An Expert System to solve this problem has been chosen in the light of the difficulties following:

. Decision-making rules are numerous. These rules are related to the reservoir data, which themselves are numerous. The type of reservoir, its depth, its pressure. the permeability and porosity of the rock, etc., must be known. Moreover, we do not always need the same data to assess the applicability of a particular process. For example, the acid number of the oil in place is a screening criterion only for certain chemical processes.

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