Streamline-Based Production-Data Integration in Naturally Fractured Reservoirs

Abstract

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 89914, "Streamline-Based Production-Data Integration in Naturally Fractured Reservoirs," by Mishal Al-Harbi, SPE, Hao Cheng, SPE, Zhong He, and Akhil Datta-Gupta, SPE, Texas A&M U., prepared for the 2004 SPE Annual Technical Conference and Exhibition, Houston, 26-29 September. Streamline-based models have shown great potential in reconciling high-resolution geologic models with production data. Use of streamline-based production-data integration has been extended to naturally fractured reservoirs. A dual-porosity streamline model was used for fracture-flow simulation by treating the fracture and matrix as separate continua connected through a transfer function. The sensitivities that define the relationship between reservoir properties and the production response in fractured reservoirs were computed analytically. The production-data integration was carried out with a generalized travel-time inversion. Introduction Natural fractures play a significant role in subsurface flow and transport of fluids. Seismic imaging and horizontal drilling have revealed the extent of fractures in many reservoirs and enabled operators to use novel ways to use fracture connectivity to enhance recovery. The number of reservoirs that are considered naturally fractured has risen significantly, increasing the need for robust fracture-characterization methods that integrate both static and dynamic data. Discrete-fracture-network (DFN) techniques map fracture planes in 3D space by use of statistical properties of fracture swarms, fracture-network geometry, and flow characteristics. DFN models can incorporate complex-fracture patterns by use of field-data sources such as cores, well logs, borehole images, seismics, and geomechanics. Although the DFN models can reproduce very realistic fracture geometry, these models must be conditiond to dynamic data (such as well-test, tracer, and production data) to reproduce the flow behavior in the reservoir. Such conditioning is particularly important for fractured reservoirs because only a few of the fractures in the DFN model might carry most of the fluid flow. Streamline models have shown great potential in integrating dynamic data into high-resolution geologic models. Streamline models can determine the sensitivity of the production data to reservoir parameters such as porosity and permeability. These sensitivities are partial derivatives that quantify how the production response will be affected by changes in reservoir properties. Typically, integrating dynamic data into reservoir models involves solving an inverse problem in which sensitivities play a key role. Streamline-based sensitivities were used in conjunction with a generalized travel-time-inversion method to integrate production data into geologic models.