Estimation of Stimulated Reservoir Volume Using the Concept of Shale Capacity and its Validation with Microseismic and Well Performance: Application to the Marcellus and Haynesville

Abstract

Abstract To reduce our dependence on microseismic data which is only available in about 5% of the shale wells, a recently developed workflow based on "hard" Geophysical and Geological data is used for the estimation of SRV and its varying rock properties in a reservoir simulator. This workflow relies on the use of the concept of Shale Capacity which encompasses the four key shale drivers responsible for most of the factors affecting the shale well performance: TOC, Brittleness, Fracture Density and Porosity. The shale capacity is available over the entire 3D reservoir volume and is estimated from well and seismic data. The SRV varying enhanced permeability is estimated through the use of a variable Half fracture length, a radial function and the shale capacity thus providing a realistic distribution and values to the reservoir simulator. Using appropriate gridding techniques such as the Tartan grid for the SRV cells, near-wellbore effects are accounted for along with no-Darcy effects and gas desorption in the shale reservoir. With these key factors represented in the dynamic model around the well, a Haynesville gas, water rate and pressure was successfully matched without the need for any major history matching effort. The resulting irregular and asymmetric SRV region and pressure distribution takes into account the geologic variability which has major implication on the EUR and well spacing. When comparing the EUR estimated from the derived geologically constrained model and those computed from traditional decline curve analysis, shale operators could be booking reserves that could be 50% lower than the actual ones. Finally, the spacing of the laterals could be optimized by taking into account the resulting irregular and asymmetric pressure distribution around the shale wells.