Unconventional Asset Development Work Flow in the Eagle Ford Shale

Abstract

Abstract The Eagle Ford Shale is recognized as the largest oil and gas development in the world, based on capital investment (Wood Mackenzie 2012). Development typically consists of horizontal wells stimulated with multiple hydraulic fracture stages. Almost $30 billion will be spent developing the play in 2013, and optimizing the completion design and spacing of these wells can result in large rewards for the companies involved. This paper presents a pragmatic integrated workflow, used to optimize development and guide critical development decisions in the Black Hawk field, Eagle Ford Shale. Geoscientists, reservoir, and completion engineers worked collaboratively to identify the optimal completion designs and well spacings for development focus areas. Multiple simplistic simulation models were history matched to existing production wells. Wide uncertainty exists in many key reservoir and completion parameters. Using stochastic realizations from ranges of key properties, uncertainty was reduced using the history matching process. The resulting calibrated reservoir scenarios formed the basis of optimization studies for development drilling and down spacing. Completion design parameters, including fracture stage length, perforation clusters per stage and landing point for the lateral, were evaluated in hydraulic fracture models. The resulting fracture geometries were simulated and the optimum completion design, and well spacing determined for each area. The optimal development was shown to vary by region, due to changing reservoir, fluid and geomechanical properties. The use of multiple subsurface realizations, spanning an appropriate range of uncertainty, was critical to the success of this study. Economic analysis across a range of potential outcomes enabled robust development decisions to be made. As a result of this work, field trials to test proposed changes to the completion have been initiated, and development drilling plans updated to reflect the optimal well spacing for each lease.