Integration of Seismic Anisotropy and Reservoir Performance Data for Characterization of Naturally Fractured Reservoirs Using Discrete Feature Network Models

Abstract

This dissertation presents the development of a method for quantitative integration of seismic (elastic) anisotropy attributes with reservoir performance data as an aid in characterization of systems of natural fractures in hydrocarbon reservoirs. This new method incorporates stochastic Discrete Feature Network (DFN) fracture modeling techniques, DFN model based fracture system hydraulic property and elastic anisotropy modeling, and non-linear inversion techniques, to achieve numerical integration of production data and seismic attributes for iterative refinement of initial trend and fracture intensity estimates. Although DFN modeling, flow simulation, and elastic anisotropy modeling are in themselves not new technologies, this dissertation represents the first known attempt to integrate advanced models for production performance and elastic anisotropy in fractured reservoirs using a rigorous mathematical inversion. The following new developments are presented:• Forward modeling and sensitivity analysis of the upscaled hydraulic properties of realistic DFN fracture models through use of effective permeability modeling techniques. iv• Forward modeling and sensitivity analysis of azimuthally variant seismic attributes based on the same DFN models.• Development of a combined production and seismic data objective function and computation of sensitivity coefficients.• Iterative model-based non-linear inversion of DFN fracture model trend and intensity through minimization of the combined objective function.This new technique is demonstrated on synthetic models with single and multiple fracture sets as well as differing background (host) reservoir hydraulic and elastic properties. Results on these synthetic control models show that, given a well conditioned initial DFN model and good quality field production and seismic observations, the integration procedure results in convergence of both fracture trend and intensity in models with both single and multiple fracture sets. Tests show that for a single fracture set convergence is accelerated when the combined objective function is used as compared to a similar technique using only production data in the objective function.Tests performed on multiple fracture sets show that, without the addition of seismic anisotropy, the model fails to converge. These tests validate the importance of the new process for use in more realistic reservoir models.

Shear fracture direction and mechanical characteristics of the middle Yanchang Formation, southern Ordos Basin, China

“…由于纵 波垂直于裂缝带传播会有衰减和旅行时延迟, 以及 反射强度降低和频率降低的现象 [12] . 沿裂缝走向地 震纵波随炮检距衰减慢, 垂直裂缝走向纵波衰减快, 且裂缝密度越大衰减越快 [13,14] . 因此可以通过分析 [9] , 受远程统一应力场的控制以及岩性和 层厚等因素共同影响 [21,22] .…”

Characterization of fractured reservoirs using a consistent stiffness-permeability model: focus on the effects of fracture aperture

“…Historically, there have been relatively few attempts to make use of such correlations in the context of fractured reservoir characterization (but see King, 2002;MacBeth and Pickup, 2002;Rogers et al, 2003;Will et al, 2005;Rasolofosaon and Zinszner, 2002;Pyrak-Nolte and Morris, 2000;Jakobsen et al, 2007a, b;Shahraini et al, 2010). More specifically, seismic anisotropy can be used to determine the orientation of fractures (Sayers 2009).…”

“…Variations in elastic properties of rocks caused by fractures are detectable in certain special seismic attributes such as variation of amplitude with azimuth, shear-wave birefringence and azimuthal variation of propagation velocity for the fractured interval (Crampin et al, 1980;Lynn et al, 1995: Lynn et al, 1999Zhu et al, 2004;Will et al, 2005). The purpose of seismic modelling in this thesis was to obtain attributes which are sensitive to the presence of aligned inclusions (fractures or deformation bands).…”

Hydraulic Parameter Generation Technique Using a Discrete Fracture Network with Bedrock Heterogeneity in Korea

“…Over the past several decades, the discrete fracture network (DFN) model has been utilized to characterize natural discrete fracture networks in relation to nuclear facilities [1][2][3], underground petroleum-storage systems [4,5], and enhanced geothermal systems [6,7]. The DFN model can simulate 2-or 3-dimensional networks of discrete features governing flow and transport, as well as partial or complete flow barriers or conductors (e.g., faults and argillaceous layers).…”