COLORADO SCHOOL OF MINES
RCP Newsletter
Reservoir Characterization Project
FALL 2026 / SPONSOR NEWS & RESEARCH
Dear RCP Sponsors,
Welcome to the updated RCP Newsletter! Building on the monthly newsletters Melinda Gale shared with our sponsor community, we are introducing a new format and moving to a quarterly update schedule aligned with the academic calendar. Each issue will bring together recent RCP news, research project progress, and student updates.
Newsletters will arrive in October, January, and March, followed by our sponsor meetings in May. We hope this format helps you follow our research and stay connected with the students behind it.
In this issue, we recognize Melinda’s contributions, introduce the agentic AI workflows we are building for reservoir characterization, and invite your participation in shaping our next field projects. Thank you for your continued support of our students and research.
Thank You, Melinda
Melinda Gale retired from her role as RCP Program Manager on September 1, 2026. Many of you worked with Melinda through sponsor meetings, membership coordination, and the monthly newsletters that kept our community connected. We are grateful for her dedication and the care she brought to supporting our students, faculty, and sponsors.
Please join us in thanking Melinda and wishing her a wonderful retirement! During this transition, please contact Jin or Ali directly with RCP questions or requests.
Building Agentic AI Workflows for Reservoir Characterization
RCP is accelerating its adoption of AI agents and developing agentic workflows for reservoir characterization. Our goal is to help researchers move more efficiently from field data to useful insights while maintaining scientific rigor and geophysical judgment.
Building on our ongoing Fasken work, we are developing workflows in which AI agents assist with data organization, coding, quality control, visualization, and documentation. We are also testing their built-in vision capabilities to assess and interpret geophysical results, including seismic images and diagnostic plots.
We are also using agents to develop reusable agentic skills and tools that capture our research findings, methods, and workflows. These resources will help us transfer research knowledge to sponsors more efficiently and make it easier for sponsor teams to apply and adapt RCP workflows to their own datasets.
Students and faculty will guide the research questions and critically evaluate the agents’ outputs and interpretations. We look forward to sharing examples and discussing where these capabilities could be most useful to sponsors.
Help Shape Our Next Research Phase XXII: July 2027–December 2029
We invite sponsors to share potential field datasets and research challenges for RCP’s next phase, running from July 2027 through December 2029.
Field data are central to RCP’s research model. Working with sponsors, we identify practical reservoir characterization questions and develop complementary student research projects around a shared field dataset. This approach allows students to integrate different types of observations, develop and test new methods, and bring their findings together to build a more complete understanding of the reservoir. Sponsors help guide the research and benefit from the resulting insights, methods, and workflows.
We welcome opportunities involving seismic, well logs, geological information, production and completion records, fiber-optic measurements, or combinations of these data. If your organization has a potential field case, please contact Jin or Ali to discuss the research questions, available data, and sharing arrangements.
Student Research Updates
Our students share recent progress across RCP’s field projects and research methods, beginning with Fasken Oil & Ranch, our main phase project.
Fasken Oil & Ranch
Aini Mokhdhari · MS, 3rd semester
Predicting mineral volumes from seismic data
Aini is evaluating machine-learning methods to predict clay and calcite volumes from seismic inversion products, supporting well placement and completion decisions. Recent quality control identified redundancy among elastic attributes, helping refine feature selection and strengthen validation of the mineral-prediction workflow.
Michael P. Braunscheidel · PhD, 7th semester
Connecting geology with fracture behavior
Michael integrates seismic and well observations to characterize carbonate mass-failure deposits and their influence on reservoir performance. Recent collaboration with RCP colleagues has linked features such as displaced carbonate blocks and debris aprons to DAS observations of hydraulic-fracture behavior, strengthening the connection between geological interpretation and completion diagnostics.
Kaitlyn Bryant · MS, 3rd semester
Investigating controls on hydraulic-fracture growth
Kaitlyn combines low-frequency DAS and microseismic observations to investigate how local geology and completion design influence fracture propagation. She is currently aligning microseismic events with DAS interpretations to evaluate inferred growth patterns and help inform completion design and well spacing.
Muhammad Reza Nasution · MS, 3rd semester
Imaging fractures with DAS-recorded microseismicity
Reza is developing a workflow to image fracture development over time using microseismic events recorded by DAS. He has begun integrating datasets and analyzing waveforms, with current efforts focused on selecting high-quality observations and distinguishing reflected from direct S-waves before proceeding to fracture imaging.
Seafloor DAS Monitoring
Chuang Xiao · PhD, 7th semester
Verifying the amplitude fidelity of seafloor DAS
Chuang is investigating the amplitude fidelity of seafloor distributed acoustic sensing (DAS) measurements to support reliable offshore seismic monitoring. He is comparing field observations with analytical and 3D simulations to evaluate how faithfully DAS amplitudes represent the seismic wavefield and how seafloor geometry, fiber burial, and coupling influence that fidelity.
Edvard Grieg
Roman Yermakov · PhD, 8th semester
Improving seismic inversion accuracy
Roman is developing seismic modeling and inversion methods for conditions where conventional approximations lose accuracy. His recent modeling produced a closer match to Edvard Grieg observations, particularly at far angles, offering a promising basis for improving estimates of shear impedance and density.
Bakken Mariner
Shenyao Jin · PhD, 7th semester
Estimating hydraulic fracture flow properties from strain
Shenyao is developing a workflow that matches fluid-flow and rock-deformation models to distributed strain measurements to estimate fracture permeability. He recently completed a field-data history match that reproduces the main spatial and temporal strain patterns, establishing a foundation for estimating directional fracture permeability during production.
Methods Supporting Multiple Field Projects
Reinaldo Sabbagh · PhD, 7th semester
Integrating multicomponent data in elastic FWI
Reinaldo is investigating how four-component ocean-bottom data can improve P- and S-wave velocity estimates through elastic full-waveform inversion (FWI). He recently implemented an energy-weighted objective function that balances hydrophone and geophone contributions, enabling their combined use in the inversion.
Hoang Anh (Ben) Nguyen · PhD, 7th semester
Advancing seismic computing
Ben is developing an elastic FWI framework that scales across multiple GPUs and computing nodes to reduce the cost of field-scale inversion. Alongside this work, he developed a quantum-circuit wave simulator with absorbing boundaries, a step toward more realistic seismic simulations using quantum computing.
Donglin Zhu · PhD, 9th semester
Developing an adaptive seismic denoising agent
Donglin is building an AI agent to diagnose noise, select processing tools, tune parameters, and assess signal preservation. He recently completed the workflow design, including feedback that guides the agent to accept a result, refine processing, or request expert review, laying the foundation for implementation and testing.
Enhanced Geothermal System (DOE-funded)
Cameron Grant · MS, 3rd semester
Characterizing fluid pathways
Cameron uses low-frequency DAS to estimate the hydraulic diffusivity of faults and fractures, helping assess pathways that could cause geothermal short circuiting and early thermal breakthrough. Recent results indicate that fast, one-dimensional analytical models can capture the pressure-driven responses studied, opening opportunities for efficient assessment of individual flow pathways between wells.
Let’s Stay Connected
We are not planning a December workshop this year, but we encourage sponsors to stay in touch. We welcome individual discussions about current research, your team’s technical priorities, and opportunities for future collaboration.
If you would like to connect with us or learn more about a student’s project, please contact Jin or Ali directly. Your feedback helps guide RCP’s research and connect our students’ work with industry needs. We look forward to continuing these conversations and seeing you at our sponsor meetings in May.
Best regards,
Jin and Ali
RCP Co-Directors
Colorado School of Mines
Reservoir Characterization Project · Colorado School of Mines
gjin@mines.edu
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