The Midland Basin Wolfcamp play is in the early stages of the development lifecycle, and provides a valuable opportunity to leverage production data from early delineation testing into a statistically valid model for predicting future horizontal production. In 2012 Laredo began testing methods of integrating geophysical, geological, petrophysical, completion, drilling, and production data to regionally high-grade drilling targets across their Permian Basin asset. Bi-variate analysis revealed that higher resolution multi-variate statistics were necessary in order to develop a local scale model that could forecast production. Utilizing multivariate statistical analytics on 82 seismic attributes (pre-stack, post-stack, and inversion), Laredo has created an "Earth Model" based on the combination of 5 seismic attributes in order to predict cumulative oil production volumes of horizontals at a set point in time. Historical well performance was then used for calibration. The model is normalized relative to completion length, completion testing, and spacing from the calibration data to understand the variations of the formation drivers on production.
The results of the model have undergone further refinement using microseismic, petrophysical, and empirical data, all of which ground truth the results to primary geological drivers of production. The model was confirmed utilizing a population of blind test wells which resulted in a correlation 0.85 of actual versus predicted cumulative 90-day oil production.
The goal of Laredo's Earth Model is to improve well performance by drilling high-potential landing points and maximizing lateral length in the most productive portions of the formation. This technique, based on high quality 3D seismic, can be utilized in any unconventional play where good sample sizes of production are available in order to high grade drilling inventories and improve individual well performance.
Attempts in utilizing conventional mapping and high grading techniques on the Wolfcamp Shale of the Midland Basin have yielded regional graded areas that do not have the capability of delineating local variation that is sub scaled to the open hole log distribution. Due to the Wolfcamp Shale thickness requiring multiple landing points to fully develop the asset, the problem of ranking and high grading not only regional areas, but vertical development is paramount.
