Sealed Wellbore Pressure Monitoring (SWPM) and Calibrated Fracture Modeling: The Next Step in Unconventional Completions Optimization

Author:

Olson Karen1,Merritt Joshua1,Barraez Rair1,Fowler Garrett2,Haffener Jackson3,Haustveit Kyle3

Affiliation:

1. Well Data Labs

2. ResFrac Corporation

3. Devon Energy

Abstract

AbstractSealed Wellbore Pressure Monitoring (SWPM) has been utilized across North and South America Basins with over 16,000 stages monitored as of June 2022. Since May 2020, the analysis procedure has been automated using a cloud-based software platform designed to ingest, process, and analyze high-frequency hydraulic fracturing data (Iriarte et al., 2021). A real time option of SWPM was also developed to aid in real time fracturing decisions (Ramirez et al., 2022).The latest development is the added capability of a fracture model that can automatically history match the volume to first responses (VFRs) determined from SWPM. This next level allows for the matching of the VFRs and the visualization of the resulting fracture geometries from a fully-coupled fracture propagation, reservoir, and geomechanics simulator. The simulator is capable of accounting for complex processes such as poroelastic stress changes from depletion, allowing for evaluation of complex interactions of fracture propagation and depletion. Insights gained from this process allows the operator to optimize their completion design faster and with fewer field trials.This paper’s focus is a case study of the DOE Eagle Ford refracturing project where a range of completion designs were trialed while monitoring offset SWPM and fiber optic strain. The resulting VFRs of the SWPM project were compared to the fiber data and then used to calibrate the fracture model. Fracture model calibration was first performed assuming that restimulation fractures propagated independently of the previously created fractures. The VFR of each stage design was calculated and summarized. The model is constructed with three stage designs primarily identified by cluster count: 7-clusters, 12-clusters, and 22-clusters. The VFR for the 7-cluster stage design was then used as an objective in an automated history matching algorithm employing the fracture model. The resulting best fit model was then evaluated on VFRs for the 12 and 22-cluster stage designs.The results demonstrate the model calibrated to the VFR of the 7-cluster stage design was able to predict VFRs in the far field for 12 and 22-cluster stage designs. Further, it is shown that including the original fractures in the model and allowing crossflow between the original and newly created fractures can match the rapid VFRs observed on a minority of stages. These same results were confirmed by the fiber data (not shared with modelers prior to calibration).Conclusions of the DOE project will show the optimum cluster spacing, cluster count and stage spacing as confirmed by the SWPM analysis and the fracture modeling.

Publisher

SPE

Reference20 articles.

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