Shale Value provides unique predictive analysis based on reservoir engineering and PVT analysis to evaluate and optimize shale and tight oil assets. Shale value delivers industry-first truly integrated commercial and technical analyses by utilizing compositional reservoir simulations, proprietary PVT models and machine learning.
Predicting long-term well performance, especially CGR/GOR trends accurately can yield significant competitive advantage. Shale Value’s analysis uniquely blends cutting-edge PVT knowledge, reservoir engineering principles and artificial intelligence to provide forecasts of well production, detailed NGLs analysis & fluid compositions, acreage and frac benchmarking.
Inferred rock, fluid and completion properties allow to distinguish between the impact of reservoir properties and fracture effectiveness on well performance.
Objective benchmarking of acreage and completion quality.
Understand changes in CGR/GOR, NGLs and fluid composition through time.
Estimate impact of changes in completion effectiveness on well performance.
Quantify NPV, production and EUR upside from adopting leading-edge completion practices.
Design optimum fracs by incorporating impact of fluid PVT behavior on well performance.
Customize frac designs by considering vaying reservoir and fluid property variations across acreage
Understand the impact of spacing on well performance and relationship between completions and spacing.
Determine optimum well spacing for a given commodity price deck, completion type and well cost.
Estimate the impact of vintaging on well performance
Estimate Net Asset Value (NAV) using Integrated fiscal models and economics tools.
Analysis of key operator positions across major shale and tight oil plays.
Phani Gadde has over 20 years’ experience in the energy industry. Most recently, Phani was a Principal Analyst in the Upstream Lower 48 team at Wood Mackenzie where he led North America supply data analysis and developed production forecasts for tight oil and shale gas plays. Before joining Wood Mackenzie, Phani worked as a research engineer at The University of Texas at Austin for six years where he led research and consulting related to produced water reinjection and slick-water fracturing in tight sands. Phani holds a B.S. from Indian School of Mines and an M.S. from the University of Texas at Austin, both in Petroleum Engineering.
Ashish Dabral has over 20 years of experience in Reservoir Engineering, including 12 years of experience with shale and tight oil reservoirs. Prior to his current role, Ashish was a Reservoir Engineering Advisor at EOG Resources and was responsible for analyzing shale plays like, Bakken, Eagle Ford, and Permian. He has worked for Shell E&P for 7 years and was subject matter expert (SME) for unconventional reservoir engineering, pressure transient analysis and PVT analysis. He began analyzing shales from the early Barnett days, while working for EOG Resources in 2003-04. He has B.S. from Indian School of Mines, and M.S. from Stanford University, both in Petroleum Engineering.
FIRM (Forecasting through Inferred Reservoir Modeling) is an industry-first reservoir engineering based analysis for shale and tight oil for forecasting well performance. FIRM infers completion effectiveness, fluid and reservoir quality using compositional reservoir simulations and artificial neural network analysis. FIRM delivers sophisticated forecasting of well performance for various fluid qualities, drawdowns, completion designs and well spacing. FIRM supports superior benchmarking and optimizing asset values under different price and cost scenarios.
FACET (Fluid Analysis and Composition Estimation Tool) uses patent-pending PVT algorithms and public domain data to provide play-wide PVT properties and initial insitu fluid composition estimation for shale and tight oil plays. FACET blends PVT analysis* with machine learning to provide accurate PVT estimates for any shale, any well and in any zone. Trained FACET models require basic inputs that are available for every well in each play.