Streamline-Based Production Data Integration With Gravity and Changing Field Conditions

Abstract

Recently, streamline-based flow simulation models have offered significant potential in integrating dynamic data into highresolution reservoir models. A unique feature of the streamlinebased production data integration has been the concept of a traveltime match that is analogous to seismic tomography, allowing the use of efficient and proven techniques from geophysics. In this paper, we propose a generalized travel-time inversion method for production data integration that is particularly well-suited for large-scale field applications with gravity and changing conditions. Instead of matching the production data directly, we minimize a travel-time shift derived by maximizing a cross-correlation between the observed and computed production response at each well. There are several advantages of our proposed method. First, it is general and extremely computationally efficient. The traveltime sensitivities can be computed analytically with a single forward streamline simulation that can be much faster than a conventional reservoir simulator. Second, it is robust and the minimization is relatively insensitive to the choice of the initial model. Finally, it is field-proven because we utilize established techniques from geophysical inverse theory.We demonstrate the power and utility of our proposed method using synthetic and field examples. The synthetic examples include a large-scale 3D example with a quarter-million grid cells involving infill drilling and pattern conversions. The field example is from the Goldsmith San Andres Unit (GSAU) in West Texas and includes multiple patterns with 11 injectors and 31 producers. Starting with a reservoir model based on well-log and seismic data, we integrate water-cut history for 20 years in less than 2 hours on a PC.

A Development of Markov Chain Monte Carlo History Matching Technique for Subsurface Characterization

“…(Pesti et al, 1993;Hyndman et al, 1994;Ezzedine et al, 1999;Yoon et al, 2001;He et al, 2002;Kretz et al, 2004;Will et al, 2005;Jeong et al, 2014). 현재 이용되고 있는 지구통계 기법으로는 크리깅(kriging)으로 대표화되는 선 형 지구통계 모델과 비선형 모델이 있으며 이들에 기초한 추계론적 모사기법들이 있다 (Deutsch and Journel, 1998).…”

Streamline-Based Production Data Integration in Naturally Fractured Reservoirs

“…4,5 Streamline models have shown great potential in integrating dynamic data into high resolution geologic models. [6][7][8][9][10] A unique feature of streamline models has been the ability to efficiently compute the sensitivity of the production data to reservoir parameters such as porosity and permeability. These sensitivities are partial derivatives that quantify how…”

“…In our previous works, we have utilized the streamline-based sensitivities in conjunction with a generalized travel time inversion method to efficiently integrate production data into geologic models. 7 Our approach has been successfully applied to a large number of field cases including a giant middleeastern carbonate reservoir. 8 Until recently, streamline models have been limited to single porosity systems and thus, were not suitable for modeling fluid flow in fractured reservoirs, particularly accounting for matrix-fracture interactions.…”

“…21 The approach has been shown to be computationally efficient, robust and suitable for large-scale field applications. 7,22 The unique aspect here is the extension and validation of streamline-based analytic travel time sensitivity computations for fractured medium and accounting for matrix-fracture exchange mechanisms. The travel time sensitivities can be applied to both streamline and finite difference simulators.…”

“…7,21 In the generalized travel time approach, which is an average travel time match, we seek to find the best overall match between observed and calculated response by systematically shifting the response on the time scale. The travel time approach is more robust and efficient than the traditional amplitude approach where we try to match the data directly.…”