_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 204162, “Multiwell-Pressure History Matching in Delaware Play Helps Optimize Fracturing for Subsequent Pads,” by Roberto Suarez‑Rivera, SPE, and Rohit Panse, W.D. Von Gonten Laboratories, and Javad Sovizi, Baker Hughes, et al. The paper has not been peer reviewed. _ Because hydraulic fracture models include complex physics and uncertainties defined by many variables, the problem of calibrating modeling results with field responses is ill-posed. It is always possible to find a calibrated model that reproduces field data; however, such a model is not unique and multiple matching solutions exist. The objective and scope of the complete paper is to define a work flow for constraining these solutions and obtaining a more-representative model for forecasting and optimization. Introduction In this project, a work flow is presented that uses an ultrafast hydraulic fracturing model with well-known physics and high-confidence rock-property inputs to conduct sensitivity analysis for pad-scale field development. Based on a study of uncertainty on the model variables, the two most-uncertain variables (tectonic strain and leakoff multiplier) are selected for model calibrations. Model results are compared with the field response for all wells and all stages to better understand the discrepancies between the field and the model. Pressure history matching (PHM) is then conducted by adjusting the selected two variables until the global error of all stages and all wells is minimized. The results are nonunique, and uncertainty in the fracture geometry remains high. This can only be reduced by including geometrical constraints from appropriate field measurements. The authors propose that the global response represents the behavior of the entire pad and is unbiased by the behavior of single specific stages. Pad Layout and Model Development The pad in question is in the Delaware Basin and targets two landing zones in the Wolfcamp A formation. The cored well used to generate the geomodel is approximately 2 miles from this pad. Rock-properties modeling was conducted at centimeter-scale resolution using core measurements and petrophysical measurements. These measurements subsequently were integrated with depth-specific measurements of static elastic properties and ultrasonic velocity measurements conducted at elevated stress conditions, representative of the in-situ effective stress. Combining the P- and S-wave velocity and elastic moduli measurements at in-situ stress conditions with the corresponding centimeter-scale resolution velocity measurements along the core surface allowed later correction of in-situ conditions for static-to-dynamic effects and acquisition of centimeter-resolution profiles of anisotropic velocities and corresponding static anisotropic elastic properties along the length of the core. A detailed interface geologic study also was conducted to identify the presence, type, geologic origin, and density of all interfaces present in the core. The core-based measurements provide a high-confidence, high-resolution vertical representation of the reservoir (at the core location). Using multiple wells with consistent field logs and consistent formations tops in the region, a regional geomodel was created for hydraulic fracture modeling. This model possessed a high-confidence representation of the structural geometry of the dominant formations represented in the model. Using these as geometrical boundaries, rock properties were propagated homogeneously along the lateral extent of the model. The authors aim to maintain the model as simply as possible, particularly when no information exists to do otherwise. Their strategy is to start with a simple model, verify the differences between the model and the field measurements, and make changes when necessary if the differences are unacceptable, but not before.
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