Deborah Sacrey

Sr. Geoscientist

Deborah Sacrey is a geologist/geophysicist with 41 years of oil and gas exploration experience in the Texas, Louisiana Gulf Coast, and Mid-Continent areas of the US. Deborah specializes in 2D and 3D interpretation for clients in the US and internationally.

She received her degree in Geology from the University of Oklahoma in 1976 and began her career with Gulf Oil in Oklahoma City. She started Auburn Energy in 1990 and built her first geophysical workstation using the Kingdom software in 1996. Deborah then worked closely with SMT (now part of IHS) for 18 years developing and testing Kingdom. For the past eight years, she has been part of a team to study and bring the power of multi-attribute neural analysis of seismic data to the geoscience community, guided by Dr. Tom Smith, founder of SMT. Deborah has become an expert in the use of the Paradise® software and has over five discoveries for clients using the technology.

Deborah is very active in the geological community. She is past national President of SIPES (Society of Independent Professional Earth Scientists), past President of the Division of Professional Affairs of AAPG (American Association of Petroleum Geologists), Past Treasurer of AAPG and Past President of the Houston Geological Society. She is currently the incoming President of the Gulf Coast Association of Geological Societies (GCAGS) and is a member of the GCAGS representation on the AAPG Advisory Council. Deborah is also a DPA Certified Petroleum Geologist #4014 and DPA Certified Petroleum Geophysicist #2. She is active in the Houston Geological Society, South Texas Geological Society and the Oklahoma City Geological Society (OCGS).

Published Work by Deborah Sacrey

Solving Interpretation Problems using Machine Learning on Multi-Attribute, Sample-Based Seismic Data

Solving Interpretation Problems using Machine Learning on Multi-Attribute, Sample-Based Seismic Data

Deborah Sacrey of Auburn Energy hosts a webinar addressing challenges like interpretation of thin bedded reservoirs far below conventional seismic ...
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Solving Interpretation Problems using Machine Learning on Multi-Attribute, Sample-Based Seismic Data

Solving Interpretation Problems using Machine Learning on Multi-Attribute, Sample-Based Seismic Data

Deborah Sacrey, Owner and Geophysicist of Auburn Energy, provides a review of the various attribute categories and their possible machine ...
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Using Self-Organizing Maps to Define Seismic Facies

Using Self-Organizing Maps to Define Seismic Facies

Using multiple attributes to evaluate a 3D volume in offshore South America containing unexpected high pressure zone and the application ...
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Visualization and Characterization of Paleozoic (Ordovician-Devonian) Tight Carbonate Reservoirs, Oklahoma, Part 1

Visualization and Characterization of Paleozoic (Ordovician-Devonian) Tight Carbonate Reservoirs, Oklahoma, Part 1

Part 1 of a 2-part Paradise Application Brief series demonstrating better well planning, identifying more productive perforation intervals and aiding ...
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Visualization of tight carbonate reservoirs

Visualization and Characterization of Paleozoic (Ordovician-Devonian) Tight Carbonate Reservoirs, Oklahoma, Part 2

Part 2 of a 2-part Paradise Application Brief series applying multiple seismic attributes to enable easy high-grading of leaseholds, asses ...
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Self Organizing Map SOM - Attributes

Using Self-Organizing Maps to Explore the Yegua in the Texas Gulf Coast

Exploring shallow Yegua formation as an independent method to accurately identify anomalies and exposing direct hydrocarbon indicators using Self-Organizing Map ...
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