Practical Aspects of Upscaling Geocellular Geological Models for Reservoir Fluid Flow Simulations: A Case Study in Integrating Geology, Geophysics, and Petroleum Engineering Multiscale Data from the Hunton Group

Benmadi Milad, Sayantan Ghosh, Roger Slatt, Kurt Marfurt and Mashhad Fahes
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Benmadi Milad: School of Geosciences, University of Oklahoma, Norman, OK 73019, USA
Sayantan Ghosh: School of Geosciences, University of Oklahoma, Norman, OK 73019, USA
Roger Slatt: School of Geosciences, University of Oklahoma, Norman, OK 73019, USA
Kurt Marfurt: School of Geosciences, University of Oklahoma, Norman, OK 73019, USA
Mashhad Fahes: Mewbourne School of Petroleum & Geological Engineering, University of Oklahoma, Norman, OK 73019, USA

Energies, 2020, vol. 13, issue 7, 1-27

Abstract: Optimal upscaling of a high-resolution static geologic model that reflects the flow performance of the reservoir is important for reasons such as time and calculation efficiency. In this study, we demonstrate that honoring reservoir heterogeneity is critical in predicting accurate production and reducing the time and cost of running reservoir flow simulations for the Hunton Group carbonate. We integrated three-dimensional (3D) seismic data, well logs, thin sections, outcrops, multiscale fracture studies, discrete fracture networks, and geostatistical methods to create a 100 × 150 × 1 ft gridded representative geologic model. We calibrated our gridded porosity and permeability parameters, including the evaluation of fractures, by history matching the simulated production rate and cumulative production volumes from a baseline fine-scale model generated from petrophysical and production data obtained from five wells. We subsequently reperformed the simulations using a suite of coarser grids to validate our property upscaling workflow. Compared to our baseline history matching, increasing the horizontal grid cell sizes (i.e., horizontal upscaling) by factors of 2, 4, 8, and 16 results in cumulative production errors ranging from +0.5% for two time (2×) coarser to +74.22% for 16× coarser. The errors associated with vertical upscaling were significantly less, i.e., ranging from +0.5% for 2× coarser to +10.8% for 16× coarser. We observed higher production history matching errors associated with natural fracture size. Results indicate that greater connectivity provided by natural fracture length has a larger effect on production compared to the higher permeability provided by larger apertures. We also estimated the trade-off between accuracy and run times using two methods: (a) using progressively larger grid cell sizes; (b) applying 1, 5, 10, and 20 parallel processes. Computation time reduction in both scenarios may be described by simple power law equations. Observations made from our case study and upscaling workflow may be applicable to other carbonate reservoirs.

Keywords: Upscaling; Error Modeling; Reservoir Modeling; Geological Modeling; Data Integration; Flow Simulation; Seismic for flow simulation; Outcrops; Carbonate; DFN; Fracture Modeling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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