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Tracking impending frac hits using sealed wellbore pressure monitoring in the Eagle Ford and Austin Chalk formations
Kowalchick, Katherine
Kowalchick, Katherine
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2022
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Abstract
Stacked plays, such as the Eagle Ford and Austin Chalk, add an additional degree of complexity in the challenges that are faced during hydraulic fracturing and field development. Incorrect well placement or a poor treatment design can lead to well-to-well interference, which can negatively impact the productivity of affected wells. Modeling a hydraulic fracturing treatment in a commercial software can help understand the geometry of the stimulated fracture network and optimize resource recovery. The addition of data from sealed wellbore pressure monitoring provides field observations on where fractures traveled to, providing novel data points to calibrate the model.
A model is only as accurate as the inputs. The geological grid must be an accurate representation of the subsurface. In this study, multi-stage hydraulic fracturing treatments on eight Eagle Ford and one Austin Chalk horizontal well were modeled. The model outputs for the Eagle Ford wells were corroborated with sealed wellbore pressure monitoring. However, a diagnostic fracture injection test was not performed on the Austin Chalk, therefore full calibration was not possible. Geological parameters from the Eagle Ford were used in the grid of the Austin Chalk well, which lead to unrealistic fracture geometries that extended into the Upper and Lower Eagle Ford. The wells in the Lower Eagle Ford were refractured during this study, however the model did not consider depletion effects or the hydraulic fracture network from the initial treatment. Data must be collected at the reservoir conditions that are being modeled to produce accurate fracture geometries. This study, and others like it in the future, could be improved with a variety of diagnostic tests, such as diagnostic fracture injection tests, to reduce the degree of uncertainty in why the model outputs and sealed wellbore pressure monitoring data vary.
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