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Demonstration of Proof of Concept of a Multi-Physics Approach for Real-Time Remote Monitoring of Dynamic Changes in Pressure and Salinity in Hydraulically Fractured Networks
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The project seeks to develop an approach to monitor changes in flow, pressure, and salinity remotely within a hydraulic fracture in near real-time based on the response of an electrically active proppant (EAP) pack. The developed methods will suggest the extent of the proppant-filled fracture, formation stress state, and fluid flow, leakoff, and invasion.


Bureau of Economic Geology (BEG) at the University of Texas at Austin - Austin, TX 78759

Sub Performers
Duke University – Durham, NC 27705
University of North Carolina – Raleigh, NC 27699


Primary recovery from a hydraulically fractured tight-oil reservoir is often a small fraction of the original oil in place ranging between 5 and 10%, possibly due to the shortcomings in the hydraulic fracture designs and the associated evaluation tools. However, the current far-field fracture diagnostic techniques, such as microseismic and tiltmeter monitoring, do not adequately detect the propped area of a hydraulic fracture (HF) or the fluid displacement. Previous works done by the Advanced Energy Consortium of the Bureau of Economic Geology (BEG) resulted in a well-characterized EAP-filled fracture at the Devine field pilot site (DFPS) and a set of validated electromagnetic (EM) codes to interrogate HF extent remotely by EM surveys.

In the current work, lab studies will be carried out to characterize the impact of salinity, pressure changes, and fluid flow on the electrical conductivity of the EAP. This information, along with host rock properties, will be used as input for solvers to discern the feasibility of detecting flow, salinity, and pressure changes at the DFPS. Once sensitivity of detection has been demonstrated in Year 1, field survey work will be conducted at the DFPS to demonstrate an approach to monitor changes in flow, pressure, and salinity remotely within a hydraulic fracture in near real-time in Year 2.


This project has several significant impacts on energy production from hydraulic fracture networks and can be applied to the subsurface applications. By enabling the optimization of refracturing processes through monitoring fracture dynamics (e.g., flow, leakoff, pressure evolution, and salinity changes), this project results in more efficient production from hydraulically fractured reservoirs. The unique and comprehensive datasets collected in this study will be disseminated to the public and will lay the foundation for the advancement of additional geophysical mapping and modeling techniques. The highly instrumented and characterized EAP-filled fracture anomaly at the DFPS can be utilized as a unique asset to conduct and validate future studies related to this project.

Accomplishments (most recent listed first)
  • Published one journal article at the Rock Mechanics and Rock Engineering journal and submitted two conference paper manuscripts at the 2023 SPE Hydraulic Fracturing Technology Conference.
  • Developed poroelastic models and pressure transient analyses for injections on January 2022.
  • Showed a dominating contribution of the streaming potential (SP) to the surface-recorded signal based on the analysis by discontinuous Galerkin frequency-domain (DGFD) EM simulation, and an SP analytical model.
  • Identified similarities between the trends of the scattered electric field recorded at the DFPS and the laboratory-recorded SP induced by flow through a proppant pack.
  • Showed a gradual response of the EAP and the instantaneous response of the sand to changes in the injection rate through laboratory measurements.
  • Developed a DGFD model of a layered medium with an inhomogeneous surface layer and considered the January 2022 source and receiver experiment configurations.
  • Executed bottomhole and surface pressure monitoring, precise flow-rate measurement, surface tiltmeter mapping, and passive wellbore distributed strain sensing (DSS) during the final EM survey at the DFPS.
  • rates, injection salinity, and duration.
  • Replaced the surface injection steel pipe with a heavy-duty polypropylene (poly) pipe.
  • Surveyed surface conductivity of topsoil, critical for the EM inversion models.
  • Conducted a pre-test to verify injectivity before the final test.
  • Validated no change in fracture signature due to previous injections by induction logging.
  • Drilled a new observation well at the southwest edge of the test site and showed by induction logging that no proppant was present at that location of the DFPS.
  • Developed a machine-learning model to perform EM inversion using synthetic data.
  • Developed laboratory models to allow injecting high-pressure fresh- or saltwater into an EAP pack.
  • Developed hydrogeological and poroelastic models using September 2020 field data.
  • Performed several injection cycles at the DFPS during first deployment.
  • Estimated that EM lab measurements can detect changes in fracture properties during injection.
Current Status

The project team attributed the scattered electric field partly to the effect of fracture dilation (inferred from the exceedance of the BHP beyond the FCP) and salinity changes. Further, the researchers have shown a clear correlation between flow rate and electric potential differences recorded by surface electrodes. These signals can be recorded in real-time. A large mismatch was observed between the EM simulation results and field observations at the beginning of the injection cycles. The contribution of the SP to the observed electric potential differences is being investigated among the possible hypotheses to explain this mismatch. The project team is constraining the forward models by the ground truth data collected from salinity as a tracer and DAS data focused on the injection time when the maximum EM response is expected. The team will then attempt to engage the inversion model to determine the fracture shape that leads to the minimum mismatch between the simulated EM results and the field data. This project scheduled to end on December 31, 2022.

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Performer Contribution


Contact Information

NETL – Scott Beautz ( or 918-497-8766)
University of Texas at Austin – Mohsen Ahmadian ( or 512-471-2999)