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Meeting presentation will be from 12:00 noon to 1:00 pm

Speaker: Dicman Alfred, Scala Energy LLC 

Well spacing and its impact on performance degradation is currently an area of critical concern in unconventional reservoirs. A new methodology to estimate well spacing from readily available data is presented. The other significant outcomes of this workflow are the ability to rank well performance and changes in geology and pressure regimes relative to an existing similarly landed producer.

At the core of this methodology is the innovative estimation of additional pressure induced from stimulation treatment long after closure when there is no more fluid leak-off into the matrix. This estimation is achieved through time dependent leak-off data that are usually available after stimulation. Multidisciplinary components like petrophysical properties, PVT, DFITs, geomechanical modeling and their uncertainties are stochastically engaged to realize the most probable stimulated rock volume (SRV).

A Delaware Basin Wolfcamp case study comprising of 10 wells is presented and the results obtained through the methodology are summarized below.

• The would-be relative underperformers were identified immediately after the frac job. 
• The local faults/ fractured zones were identified and reaffirmed with seismic and well data.
• The evaluated pressure regimes along the horizontal were corroborated by well performance.
• The estimated SRV compared well with other commercial frac geometry monitoring technology that was conducted as a part of this study. 
• The appropriate well spacing and optimum completion design to minimize well interactions were determined, specific to local geology and landing targets.

Present industry solutions to well spacing involve expensive geomechanical earth modeling or frac geometry monitoring that are time consuming, data intensive and unfortunately geography specific. The new methodology presented is quicker and requires no new data collection than those that are routinely gathered. Additional benefits of this methodology include: understanding the impact of lithology on frac growth, refine reservoir characterization to local scale, compare pressure regimes across wells/faults, and set expectations for well performance after completion.

Speaker Biography: Dicman Alfred, Scala Energy LLC
Dicman Alfred has 19 years of unique expertise in Geoscience and Engineering domains. His areas of focus include business development, petrophysical modeling, inter-discipline integration, geo-cellular modeling, analytical reservoir performance analysis and optimization, completion design, data analytics and machine learning. 

Recent experiences include serving as Director of Subsurface for SOTAOG, heading the real-time production optimization and predictive analytics group; Technical Advisor in the acreage acquisition to development for Scala Energy LLC; Senior petrophysicist with the Upstream Technology Worldwide Petrophysics group at Marathon Oil; Engineering Team lead for Eagle Ford field development and Integrated Project team lead for Woodford, Eagle Ford and Austin Chalk field studies. 

Prior to joining Marathon, he worked as a wireline field engineer for Halliburton Energy Services and as a Petroleum Engineer for Schlumberger Information Solutions. He holds a Master’s Degree in Petroleum Engineering from Texas A&M and a Bachelor’s Degree in Mechanical Engineering from Indian Institute of Technology, Chennai.

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