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Protecting Return on Investment Using the Big Loop Workflow, an Automated Ensemble Based Approach

July 17, 2018
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Presented by:  Samir Walia, Chief Geoscientist and Regional Manager for Subsurface Software Solutions
Featured Domains: Reservoir Modeling and Reservoir Engineering
Featured Technology: Big Loop


For comments or questions, please contact: Samir.Walia@emerson.com.


The sharp decline in oil prices is pushing exploration and production companies to revise future investment plans and ensure that investment decisions come with positive returns. Reservoir modeling is a key tool in the evaluations, as it explores different development scenarios to optimize field performance and gain the most value out of the reservoir. Traditional reservoir modeling, however, relies on a single or small number of scenarios (base, high and low cases) and introduces deterministic prediction profiles for future field performance that don’t fit with modern reservoir management guidelines. Such a modeling approach also fails to integrate the impact of uncertainties at the different reservoir modeling stages - from seismic interpretation to dynamic simulation. Using an integrated reservoir modeling and reservoir engineering workflow, the Big Loop and its ensemble statistics-based approach can generate crucial information to reduce risk and support decision making - in determining reservoir uncertainties and their ranges, planning future field development, and guiding well placement using multiple history match models.


Samir-Walia_sm.pngSamir Walia is Global Chief Geoscientist and Regional Manager for Subsurface Software Solutions at Emerson.  Samir has 22 years of experience in the oil and gas E&P industry.  With a Master's Degree in Geophysics from a prestigious university in India, he now specializes in Reservoir Characterization and Modeling.  His qualifications and achievements extend to his most recent contribution - automating the process of capturing and quantifying reservoir uncertainties, for more reliable reserve forecasts.