EOR Advisor System: A Comprehensive Approach to EOR Selection

Abstract

Abstract Hydrocarbon exploration is reaching global frontiers in the search for near- and long-term solutions to increase oil production from the existing assets. Enhanced oil recovery (EOR) offers a substantial alternative to improve recovery from existing and mature fields by means of enhancing pore level sweeping in the reservoir. While the principles of EOR are not new, field implementation has been scarce and as a consequence, the physics governing the displacement process have not been completely understood, nor has the screening criterion been properly defined. Several authors have proposed different binary approaches to address the issue of screening, with the drawback of different, and in some cases, contradictory screening results. This paper presents a workflow to assess the EOR applicability for a given reservoir. The backbone of the advisor system is an expert system that has been calibrated using information from a systematic data review of a newly developed global EOR project database, merged with in-house EOR engineering expertise. One of the advantages of this approach over other published EOR expert systems is the capability for handling uncertain input, which enables qualitative ranking of the applicability of various EOR methods in heterogeneous reservoirs. Moreover, is the workflow makes it possible to interrogate the expert system with incomplete input information and obtain consistent results, which enables comparative sensitivity runs to assess the most valuable additional information needed to resolve ambiguities in the EOR method ranking. The system is equipped with a comprehensive evaluation of the current static and dynamic conditions of the reservoir, and is fully linked to geological and geophysical modeling and simulation, enabling the extraction of geological-consistent input values for the expert system directly from the model to facilitate quick forecasts of highly ranked EOR methods through surrogate reservoir models. Introduction EOR screening has been discussed in different levels of complexity by different authors1–8 with different approaches postulated, ranging from applicability ranges, binary selection, data mining, and numerical simulation. Simplicity and repeatability are among the traded values during the first attempts of recognizing the best-suited EOR process for a given field, which of necessity, has increased the value of past experiences to guide and provide a "sanity check" for any EOR decision, particularly when dealing with scarce information. The screening, or selection, is a data-driven process, with the analysis details being proportional to the quality and relevance of the available information and often yielding multiple equally plausible EOR alternatives for a given field. EOR selection requires a proper understanding of reservoir architecture and dominant reservoir fluid-flow forces, making the screening process highly dependent not only on local compatibility (pore level) but also heterogeneity variations on the 3D space. A proper balance of capillary, gravity, and viscous forces during the EOR process becomes an important aspect of the field design, and subsequently of the screening process.