Quantitative Evaluation of Key Geological Controls on Regional Eagle Ford Shale Production Using Spatial Statistics Conference Paper uri icon


  • Summary Recent progress has increased our understanding of key controls on the productivity of shale reservoirs. The quantitative relations between regional Eagle Ford Shale production trends and geologic parameters were investigated to clarify which geologic parameters exercise dominant control on well-production rates. Previously, qualitative correlations for the Eagle Ford Shale were demonstrated among depth, thickness, total organic carbon (TOC), distribution of limestone beds, and average bed thickness with regional production. Eagle Ford production wells are horizontal, but it was necessary to use vertical wells that penetrated the Eagle Ford to map reservoir properties. No wells in the database had both production and geological parameters, and thus geological parameters could not be directly related to individual-well production. Therefore, spatial-interpolation methods derived from the Kriging and Bayesian methods with Markov-chain Monte Carlo (MCMC) sampling algorithms were used to integrate data sets and predict geological properties at production-well locations. The spatial Gaussian-process-regression modeling was conducted to investigate the primary controls on production. Results suggest that the 6-month cumulative production from the Eagle Ford Shale, in barrels of oil equivalent (BOE), increases consistently with depth, with Eagle Ford thickness (up to 180-ft thickness), and with TOC (up to 7%). Also, when the number of limestone beds exceeds 12, production increases with the number of limestone beds. The corresponding significance code indicates that the parameters most significant to production are TOC and depth (which relates to pressure and thermal maturation). Concepts and models developed in this study may assist operators in making critical Eagle Ford Shale development decisions and should be transferable to other shale plays.

published proceedings

  • SPE Reservoir Evaluation & Engineering

author list (cited authors)

  • Tian, Y., Ayers (ret.), W. B., Sang, H., McCain, W. D., & Ehlig-Economides, C.

citation count

  • 10

complete list of authors

  • Tian, Yao||Ayers (ret.), Walter B||Sang, Huiyan||McCain, William D||Ehlig-Economides, Christine

publication date

  • May 2018