Estimation of fracture half-length with fast Gaussian pressure transient and RTA methods: Wolfcamp shale formation case study

Abstract

Accurate estimation of fracture half-lengths in shale gas and oil reservoirs is critical for optimizing stimulation design, evaluating production potential, monitoring reservoir performance, and making informed economic decisions. Assessing the dimensions of hydraulic fractures and the quality of well completions in shale gas and oil reservoirs typically involves techniques such as chemical tracers, microseismic fiber optics, and production logs, which can be time-consuming and costly. This study demonstrates an alternative approach to estimate fracture half-lengths using the Gaussian pressure transient (GPT) Method, which has recently emerged as a novel technique for quantifying pressure depletion around single wells, multiple wells, and hydraulic fractures. The GPT method is compared to the well-established rate transient analysis (RTA) method to evaluate its effectiveness in estimating fracture parameters. The study used production data from 11 wells at the hydraulic fracture test site 1 in the Midland Basin of West Texas from Upper and Middle Wolfcamp (WC) formations. The data included flow rates and pressure readings, and the fracture half-lengths of the 11 wells were individually estimated by matching the production data to historical records. The GPT method can calculate the fracture half-length from daily production data, given a certain formation permeability. Independently, the traditional RTA method was applied to separately estimate the fracture half-length. The results of the two methods (GPT and RTA) are within an acceptable, small error margin for all 5 of the Middle WC wells studied, and for 5 of the 6 Upper WC wells. The slight deviation in the case of the Upper WC well is due to the different production control and a longer time for the well to reach constant bottomhole pressure. The estimated stimulated surface area for the Middle and Upper WC wells was correlated to the injected proppant volume and the total fluid production. Applying RTA and GPT methods to the historic production data improves the fracture diagnostics accuracy by reducing the uncertainty in the estimation of fracture dimensions, for given formation permeability values of the stimulated rock volume.