Experiences With Streamline-Based Three-Phase History Matching

Author:

Oyerinde Adedayo1,Datta-Gupta Akhil1,Milliken William2

Affiliation:

1. Texas A&M University

2. Chevron Energy Technology Company

Abstract

Summary Streamline-based assisted and automatic history matching techniques have shown great potential in reconciling high resolution geologic models to production data. However, a major drawback of these approaches has been incompressibility or slight compressibility assumptions that have limited applications to two-phase water/oil displacements only. Recent generalization of streamline models to compressible flow has greatly expanded the scope and applicability of streamline-based history matching, in particular for three-phase flow. In our previous work, we calibrated geologic models to production data by matching the water cut (WCT) and gas/oil ratio (GOR) using the generalized travel-time inversion (GTTI) technique. For field applications, however, the highly nonmonotonic profile of the GOR data often presents a challenge to this technique. In this work we present a transformation of the field production data that makes it more amenable to GTTI. Further, we generalize the approach to incorporate bottomhole flowing pressure during three-phase history matching. We examine the practical feasibility of the method using a field-scale synthetic example (SPE-9 comparative study) and a field application. The field case is a highly faulted, west African reservoir with an underlying aquifer. The reservoir is produced under depletion with three producers and more than thirty years of production history. The simulation model has several pressure/volume/temperature (PVT) and special core analysis (SCAL) regions and more than 100,000 cells. The GTTI is shown to be robust because of its quasilinear properties as demonstrated by the WCT and GOR match for a period of 30 years of production history.

Publisher

Society of Petroleum Engineers (SPE)

Subject

Geology,Energy Engineering and Power Technology,Fuel Technology

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