Explaining Well Performance Patterns: Application of Scaled Hydrocarbon Head Potential to Permian, Anadarko Basins and Eagle Ford for Better Resource Assessment and Development

Abstract

Insights into the variability of production rates and fluid properties at the pad, township and county scale will help decision makers. Testing mechanisms of the producible hydrocarbons in the Permian, Anadarko and Eagle Ford petroleum system shows encouraging results. The integration of geosciences, engineering, big data and numerical modeling is described and then demonstrated.

Many have shown that wells that outperform the average well economics correlate with the degree of overpressure and fluid properties. Several methods have been applied to map these properties at a regional scale. In Varady et al 2017, Scaled Hydrocarbon Head Potential (SHCHP) workflow for resource assessment was presented. We have applied this work to other basins as an adaptable universal tool for tight liquids and hybrid systems.

The variability in well performance in Barrels of Oil Equivalent per Day (BOE/D), Hydrocarbon Density (HC API), and Gas-Oil Ratio (GOR) deviate from in-situ maturity trends. Modifying Darcy flow parameters along carrier beds allows empirical calibration. Training sets were used to test the form of the empirical equations. Combining these empirical relationships with standard source rock expulsion and migration maps creates maps of modeled BOE/D, HC API and GOR. Optimized parameters are derived by minimizing the difference between observed and modeled.

Over 40,000 wells for the STACK/SCOOP, Wolfcamp/Bone Springs and Eagle Ford formations constrained the formulation. Each basin model is calibrated independently for burial and thermal spatial and temporal to measure a) thermal indicators and b) temperatures. The SHCHP uses a GOR-HC API density function developed by PVT analysis and equations of state (EOS). Pressure gradient at a regional scale is first obtained through a linear inverse solution. Supervised learning uses the structural evolution and geohistory to improve data fitting. SHCHP allows us to integrate and understand pressure evolution in source rocks and hybrid resources, in different depositional settings, ages, and basins that underwent complex and structural settings. The strong relationship between SHCHP and well performance allows us to 3D map between known productions and diagnose areas exhibiting phase separation in the subsurface.

We learn as much or more when the model doesn’t fit the data. Deviations between observed and modeled requires investigators to reach out for a better understanding of the depositional and structural history.

AAPG Datapages/Search and Discovery Article #90323 ©2018 AAPG Annual Convention and Exhibition, Salt Lake City, Utah, May 20-23, 2018