New Modeling and Simulation Techniques Optimize Completion Design and Well Spacing
Authors: Carpenter Chris 
Published: March 2020

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 194367, “Optimize Completion Design and Well Spacing With the Latest Complex Fracture Modeling and Reservoir-Simulation Technologies—A Permian Basin Case Study With Seven Wells,” by Hongjie Xiong, SPE, and Songxia Liu, University Lands, and Feng Feng, SPE, Texas A&M University, et al., prepared for the 2019 SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, 5–7 February. The paper has not been peer reviewed.
Proper lateral and vertical well spacing is critical for efficient development of unconventional reservoirs. Much research has focused on lateral well spacing but little on vertical spacing, which is challenging for stacked-bench plays such as the Permian Basin. Following a previous, successful single-well study in paper SPE 189855, the authors have performed a seven-well case study in which the latest complex fracture modeling and reservoir-simulation technologies have been applied. This synopsis will concentrate on the methodology behind the study; the reader is encouraged to view the complete paper for specific comparisons of completion designs.
Introduction
Complex-fracture-modeling tools are used frequently to study well spacing. Most research has focused on lateral well spacing rather than on vertical spacing, though the industry has seen many fracturing hits and hydraulic communications between wellbores placed vertically in stacked plays.
Field pilot tests have been used extensively to test and optimize lateral and vertical well spacings and to optimize well-completion designs. These pilot tests, however, take considerable time to implement and are very expensive.
In this multiple-well study, the authors used an established work flow to study the fracture interaction between wellbores and lateral and vertical well spacings. A calibrated model was then used to optimize well-completion designs for the Wolfcamp formation.
Work Flow
The work flow to build and calibrate the complex-fracture-network and reservoir-performance-simulation models, and then use the models to conduct sensitivity analysis on the fracture networks, resulted from different completion designs and corresponding well performance.
Because some critical data sets are spread throughout a wide areA&Mdash;including core data, comprehensive well-logging data, and geomechanical properties—the authors first built a regional geological model, then sliced the sector models from the regional model. This enabled use of available data that were spread sparsely across the area. On the basis of the well locations, a sector model was built by cutting a section from the regional geological model. In the process, the properties were repopulated with a finer grid size.
Previous studies discussed using the seismic data to build a discrete fracture network (DFN). For the authors of this paper, however, the DFN represents not only the natural fracture networks but also includes geological bedding or layering information. Those beddings or layerings may be mechanical-weakness connections, which influence hydraulic-fracturing propagations. The detailed well-completion information was then plugged in.
Seven-Well Case-History-Modeling Setup
Seven wells drilled and completed in four different zones within the Wolfcamp formation were studied. A sector model was cut from the full-field (regional) model on the basis of the well locations, considering the possible fracture-propagation-modeling needs. The sector model covers a length of 12,600 ft, a width of 4,200 ft, and a thickness of 3,000 ft. In the process, a much finer grid size was used (refined from 300×300 ft in the regional model to 33×33 ft in the sector model) with consideration of perforation cluster spacings. Then, all formation properties were repopulated to the smaller grid cells with the same property models used in the regional model. The wellbores and perforations then were input into the sector model.