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Advanced Monitoring and Characterization Techniques for Energy Reservoirs

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 211

Special Issue Editor

Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, China
Interests: active source exploration seismic imaging and parameter inversion; passive source microseismic monitoring and reservoir geomechanics

Special Issue Information

Dear Colleagues,

For this Special Issue, we invite original contributions that focus on energy-oriented subsurface technologies and system-level approaches supporting geothermal energy utilization, carbon capture and storage (CCUS), and subsurface energy storage. The emphasis is on studies that advance the safe, efficient, and sustainable operation of subsurface energy systems, including reservoir performance evaluation, monitoring strategies, and data-informed decision-making for energy development and management.

Contributions addressing energy-related reservoir monitoring and characterization, operational optimization, and risk mitigation in geothermal, CCUS, and subsurface energy storage projects are particularly welcome. Studies may incorporate data-driven methods, machine learning-assisted analysis, time-dependent monitoring, and integrated modeling frameworks to support energy extraction, injection, storage efficiency, and long-term system reliability.

This Special Issue aims to provide a platform for applied and interdisciplinary research that links subsurface processes with energy production, energy storage, emissions reduction, and system sustainability, ultimately supporting the transition to low-carbon and resilient energy systems.

Dr. Hao Zhang
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • reservoir characterization
  • machine learning
  • CCUS
  • unconventional reservoirs
  • geothermal energy
  • coupled modeling
  • hydraulic fracturing
  • subsurface stress

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Published Papers (1 paper)

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Research

16 pages, 1660 KB  
Article
Application and Verification of Formation Pressure Estimation for Geo-Energy Engineering Based on Flow Regime Identification Analysis of Different Injection/Shut-In Tests
by Qiuyang Xu, Yuehui Yang, Awei Li, Bangchen Wu, Hao Zhang, Ran Li, Shiyuan Li, Chongyuan Zhang, Qunce Chen and Dongsheng Sun
Energies 2026, 19(10), 2434; https://doi.org/10.3390/en19102434 - 19 May 2026
Abstract
Conventional Diagnostic Fracture Injection Tests (DFITs) are widely used for formation pressure estimation, but in practice, they frequently require days, weeks, or even months of extended shut-in periods, a challenge particularly pronounced when large injection volumes are coupled with ultra-low formation permeability. While [...] Read more.
Conventional Diagnostic Fracture Injection Tests (DFITs) are widely used for formation pressure estimation, but in practice, they frequently require days, weeks, or even months of extended shut-in periods, a challenge particularly pronounced when large injection volumes are coupled with ultra-low formation permeability. While recent studies have proposed various modified DFIT approaches to reduce testing time, direct physical validation confirming the reliability of the derived formation pressure estimates remains scarce in the literature. This study applies a low-rate/volume injection mini-frac approach that integrates flow regime identification and Horner analysis. Two complementary field cases are presented: a standard DFIT in a shale reservoir to validate the baseline methodology, and a low-volume mini-frac in a tight granite formation to demonstrate rapid estimation. Results show that low-volume injections exhibit a flow regime evolution identical to standard DFITs, yet this approach is expected to accelerate the transition to the pseudo-radial flow regime. To verify the reliability of formation pressure estimates derived from such methods, the formation pressure estimated in the low-rate/volume injection mini-frac case was benchmarked against a decade of continuous downhole fluid pressure monitoring data from the same well, yielding a relative error of less than 5%. The findings suggest that employing a lower injection rate and volume can improve formation pressure testing efficiency, with potential applications in unconventional hydrocarbon development and deep geo-energy engineering. Full article
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