Application of Using Fuzzy Logic as an Artificial Intelligence Technique in the Screening Criteria of the EOR Technologies

Abstract

Abstract Screening criteria stage for the EOR applications is useful for many candidate reservoirs before expensive reservoir descriptions and economic evaluations are done. This paper presents the application of using fuzzy logic as an artificial intelligence technique in the screening criteria of the EOR technologies. EOR screening criteria have been developed based on field results. The database of 347 successful EOR projects worldwide is used to carry out statistical analysis which resulted in determination of four critical values (minimum, maximum, r1, r2) for each fluid and rock property. The determined values identify the suitable range of the rock and fluid properties and the screening criteria for each EOR method. In addition, these ranges can rate the properties of any field under study from 0 to 1 (through fuzzy logic membership functions). The minimum and the maximum values represent the successful boundaries of the fluid or rock properties for the studied EOR method; while r1 and r2 values represent the ranges with maximum rating (best conditions) for the fluid or the rock properties. Not all fields are amenable to EOR processes. Effective screening practices must be employed to identify suitable candidates. In the developed screening tool, there are 15 inputs representing EOR screening criteria of the reservoir rock and fluid properties including: API gravity, oil viscosity, reservoir depth, rock permeability, oil saturation, reservoir temperature, formation water salinity, net pay thickness, permeability variation coefficient (representing heterogeneity index), formation type, minimum miscibility pressure, initial reservoir pressure, current reservoir pressure, fracture pressure and an option showing if the reservoir is dip or not. The developed screening tool is characterized by an easily and friendly interface with additional options comparing to the other existing software or expert systems. The proposed tool can be used to support the decision making during the critical technology selection phase. Such study is an original contribution to achieve successful EOR applications.