Summary
This paper presents the development of an integrated, multidiscipline reservoir model for dynamic flow simulation and performance prediction of a geologically complex, naturally fractured volcanic reservoir in the Shang 741 Block of the Shengli field in China. A static geological model integrates lithological information, petrophysics, fracture analysis, and stochastic fracture network modeling with Formation MicroImage (FMI) log data and advanced 3D seismic interpretations. Effective fracture permeability, fracture-matrix interaction, reservoir compartmentalization, and flow transmissibility of conductive faults are obtained by matching various dynamic data. As a result of synergy and multiple iterations among various disciplines, a history-matched dynamic reservoir-simulation model capable of future performance prediction for optimum asset management is constructed.
Introduction
The multidisciplinary approach of closely related teamwork across the disciplines of geology, geophysics, petrophysics, and reservoir engineering is now the accepted approach in the industry for reservoir management and field development.1–6Fig. 1 shows components of integrated reservoir characterization and the contribution of each discipline to the process. The strength of integrated reservoir modeling, however, can be particularly dramatized with some reservoirs that contain extreme forms of heterogeneity and unusual structural features. The Shang 741 Block of the Shengli fractured volcanic reservoirs is one such example.
The Shang 741 Block contains a series of vertically separated fractured volcanic reservoirs with different characteristics. Matrix porosity and permeability are both low in most horizons; thus, natural fractures are the main flow pathways for fluids. FMI logs delineate the orientation and density of the fracture distribution. Lithology variations, extensive compartmentalization, and looping of reservoir body units are recognized from the geologic depositional model and seismic data. Tying acoustic well data to 3D seismic data through synthetic seismograms combined with FMI information controls time and depth structure maps for a reliable geological model.
Reservoir modeling (RM) software provides a platform to integrate lithology correlations with seismically based structural features and petrophysical properties to yield a framework for a dual-porosity Eclipse** reservoir flow-simulation model. Fractures delineated and characterized from well data are stochastically distributed in the reservoir for each horizon with a fractal-based, fracture-mapping algorithm.7 Simulation of effective gridblock fracture permeability and matrix-fracture transfer function parameters are upscaled into coarse-scale simulation gridblocks. These upscaled values are verified and calibrated by available pressure-transient effective permeabilities for consistency.
In this paper, a dual-porosity reservoir-simulation model is constructed from a static geological and geophysical (G&G) model in a stepwise fashion through successive incorporation of dynamic information from pressure-transient tests, static reservoir pressure, water breakthrough behavior, and well-production performance data. Compartmentalization incorporates effects of multiple oil/ water contacts (OWC) for proper modeling of regional pressure-trend behavior. Fault conductivity or thin channel transmissibility, verified by seismic and well tests, is augmented for better modeling of water movement in the reservoir.
As a result of synergy among various G&G disciplines and incorporation of dynamic reservoir engineering data, a representative and production-data calibrated model is constructed for this reservoir. The paper shows that this is possible only through multiple iterations across the disciplines and through integrated project teams. The model also serves as a reservoir-management tool in production monitoring, in evaluating the effects of implementing pressure-maintenance injection programs, and in better understanding the impact of various uncertainties on the ultimate recovery of the field.
Database
The data sources available for this study include:Geological interpretations and geological framework model, including geological markers.Three-dimensional seismic survey data with 529 lines by 583 common depth points (CDPs) at 25-m bin size that covers a 200-km2 area.Three vertical seismic profile (VSP) surveys and their detailed interpretations.Petrophysical analysis on 13 nearly vertical wells that penetrate the reservoir horizons.FMI logs and analysis for fracture delineation.Pressure/volume/temperature (PVT) samples and analyses.Conventional and special core analysis for matrix and fracture relative permeability, matrix capillary-pressure characteristics, and rock compaction.Two single-well, pressure-buildup tests.Three interference tests.Spot static-pressure measurements.Production data, including flowing bottomhole and tubing pressure, oil, water, and gas flow rates.Extensive information from 13 drilled wells in the field.
Reservoir Characterization
Geology.
Shang 741 fractured reservoirs are located within the large Shengli field in the Bohai basin, China (Fig. 2). These volcanic reservoirs, primarily of the Oligocene Shahejie and Dongying formations, are composed of fractured basalt, extrusive tuff, and fractured diabase of intrusive origin (Fig. 3). The Shang 741 consists of a stack of separated fractured reservoirs, which communicate with each other only through drilled wellbores. These are divided into the H1, H2, H3, Lower H3, H3 1, and H4 fractured reservoir units. Fig. 4 shows the stacking order of these reservoirs along with geological markers, lithology type, and facies relationships.
Requirements of Petroelastic Models in Reservoir Characterization for Flow Simulation