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Permian Basin

About the basin

Besides being the highest oil producing sedimentary basin in the United States, the Permian Basin also contains the thickest deposit of Permian aged rocks on the planet Earth.  The Permian Basin is a composite foreland basin located largely in western Texas and extends into southeastern New Mexico.  It is composed of several constituent basins; the Midland Basin being the largest, The Delaware Basin coming in second, and the Marfa Basin, by far the smallest. 

The basin itself was initiated during the collision of Laurentia and Gondwana, from late Mississippian through the Pennsylvanian (though the Permian Basin does contain sedimentary rocks dating as far back as the Ordovician, deposited within the ancestral Tobosa Basin).  During this time the region experienced rapid subsidence, and consequently, rapid sedimentary filling.  Carbonate shelves established themselves on the north, west, and eastern margins of the Permian Basin as well as the Central Basin Platform separating the Delaware and Midland component basins, while fluvial-deltaic and marine clastics were also deposited within the basin.  Evaporites deposits such as gypsum, anhydrite, and salt formed during the late Permian, as tectonics from the breakup of Pangea limited the amount of seawater entering the Basin.

Sea level and tectonics played a huge role in the deposition of the above mentioned sediments, and oftentimes you can see thin, almost chaotic interfingering beds of carbonate, shale, and sandstone (particularly within the Wolfcamp Formation).  From a 3D modeling perspective, the facies can be quite a challenge to properly characterize.


  • Optimization of Stacked Play Development, Delaware Basin, TX   (2019)

The goal of this project was to optimize well spacing, landing, and completion design for new development throughout a client’s Delaware Basin assets in order to drill fewer wells faster and with less overlap in drainage area.  I constructed a fully automated Living Earth Model (LEM) using depth converted seismic interpretation and inversion volumes tied to available wells.  The static model properties were automatically split and resampled into into seven sector models for dynamic reservoir and geomechanical simulation.  This project was a finalist for the Conrad Schlumberger Award for Technical Depth at the 2019 Reservoir Symposium.

  • Velocity, lithology, rock property, and fracture modeling of core acreage; Midland Basin, TX (2017)

In this project, I generated a layer cake Vo velocity model based on 18 tied wells and used the velocity model to domain convert seismic inversion attributes and interpretations to depth.  I then built a deterministic model framework from the interpretations flexed to available well control and used the inversion data as a statistical driver for a hierarchal facies model with 17 nested facies classes.  I used the facies to constrain the distribution of continuous rock properties and ultimately a Discrete Fracture Network Model for dual permeability simulation.  After model completion, 10 wells withheld by the Chief petrophysicist were used to blind test model predictability.  Porosity was predicted with 85% accuracy, while Sw was predicted at 90% accuracy.  The model was ultimately used by the client for dynamic fluid flow simulation and production history matching.

  • 3D Integrated Geostatistical Reservoir Model construction and automation; Midland Basin (2016)

This project consisted of integrating data from multiple domains into a Living Earth Model (LEM), fully capable of incorporating new and refined data at the push of a button.  I analyzed 3D seismic overlapping the area and performed the seismic well tie, horizon interpretation and velocity model to convert the volume to depth.  I then incorporated seismic inversion results (Poisson’s, Young’s, VP/VS, Lambda Rho, Mu Rho), post-stack seismic attributes, HRA Petrophysical analysis, FMI, and normalized well log data to form a cohesive 3D model including lithology, porosity, permeability, water saturation, and a preliminary discrete fracture network model.  Client then conducted a blind well test to understand model predictability which resulted in a 90% success rate in lithology prediction.

  • Enterprise Data Migration and Software Deployment for midsize operator, Denver, CO. (2018)

a Midsize Denver operator with assets in both Midland and Delaware Basins had a need to standardize all G&G staff on a single software platform.  I managed the technical aspects of this several phase project, starting with a proof-of-concept pilot consisting of data provisioning and QC around core acreage, Installing the central production database, migrating data, training of all geology, geophysics, and geotechnologist staff company wide, supporting staff through initial evaluation and adoption, and eventually handing off to in-house staff after successful transition.  In all, I migrated around a terabyte of data and trained a staff of 40 geoscientists.