Numerical model illustrating flow focusingUT GeoFluids is managed by the University of Texas Institute for Geophysics (UTIG) and is currently supported by 10 energy companies at a cost of ~ $50,000/year. We are at the start of a 10-year effort entitled GeoFluids2020. Our results are used to predict pressure and stress, design stable and safe drilling programs, and predict hydrocarbon migration and entrapment. We study the state and evolution of pressure, stress, deformation and fluid flow through experiments, models, and field study:

  1. Experimental: We analyze fabric, acoustic, electrical, and material properties of mudrocks : 0.1-100 MPa.
  2. Poromechanical Modeling: We develop and apply coupled models to link realistic rheologies, deformation, stress (shear and normal), and pore pressure.
  3. Field Study: We analyze pore pressure, stress, and deformation in both conventional and unconventional basins.

We produce innovative concepts and analysis workflows that couple geology and geomechanics to predict and interpret pore pressure and stress in the subsurface. We have

  • developed online software that predicts reservoir pressure,
  • released databases and material models that describe mudrock material behavior, and
  • developed workflows to predict stress in salt systems and thrust belts.

Our new research aims to develop a unified approach that incorporates stress dependency, creep, mineralogical transformation, and loading path to illuminate the state and evolution of pressure and stress in basins. We are applying this approach to develop two and three-dimensional whole earth models that improve well design, real-time drilling, borehole stability, reservoir simulation and seismic imaging.

Click here for more details about the Consortium, or contact the Consortium Co-Directors, Dr. Peter Flemings and Dr. Jack Germaine.

Each year, UT GeoFluids holds a consortium meeting to update members on current research. The 15th UT GeoFluids Annual Meeting will take place Feb. 28 — March 1, 2024 in Austin, Texas. Lectures and workshops will be given at the University of Texas Institute for Geophysics, while our opening evening poster session and Thursday evening dinner will be held at the Lone Start Court hotel. Members register now (and find discounted hotel rates) at the 2024 Event Website, or learn more about past UT GeoFluids Annual Meetings.

Our 15th Annual Meeting will take place February 28, 2024 – March 1, 2024 in Austin, Texas. The in-person program features a reception and poster session, industry talks, hands-on workshop, and a group dinner. We look forward to your participation. Explore highlights and register: 2024 GeoFluids Annual Meeting.

New Research Published. July 2023. Maria Nikolinakou published a significant research paper simulating pore pressure in thrust belts. See News to learn more.

ExxonMobil Rejoins UT GeoFluids. July 2023. We are thrilled to have ExxonMobil back with us at UT GeoFluids.

New UT GeoFluids Grad Student. June 2023. Tolulope Agbaje joined UT GeoFluids and is working on machine learning and pore pressure prediction.

UT GeoFluids 2023 Annual Meeting. Our 14th Annual Meeting took place March 8-10, 2023, in Austin, Texas. There were approximately 50 attendees and many vibrant discussions, particularly about interpreting leak-off pressure! Thank you to everyone who participated. For more information visit Annual Meetings.

Nikolinakou Presents Research at Energy Conferences. May 2022, Maria Nikolinakou presented research at the Offshore Technology Conference 2023 in Houston, on May 2, and at the inaugural Energy Geoscience Conference 2023 in Aberdeen, on May 18. See News to learn more.

Peter Flemings is the 2024 recipient of the AAPG Robert R. Berg Outstanding Research Award. The award recognizes decades of contribution to petroleum geoscience through UT GeoFluids, including foundational work on gas hydrate systems and subsurface overpressure.

View all UT GeoFluids publications on the publications page
Members can access copies of publications at the Member Area Publication Site
If you don't know your password please contact Peter Flemings.


Portnov, A., Flemings, P.B., You, K., Meazell, K., Hudec, M.R., Dunlap, D.B., 2023, Low temperature and high pressure dramatically thicken the gas hydrate stability zone in rapidly formed sedimentary basins. Marine and Petroleum Geology.

Nikolinakou, M.A., Wang, X., Flemings, P.B., Johri, M., 2023, 3D Mad Dog Pressure and Stress Prediction Coupling Seismic Velocities, Pressure, and Stress Measurements. Offshore Technology Conference, OTC-32555-MS.

Nikolinakou, M.A., Flemings, P.B., Gao, B., Saffer, D.M., 2023, The Evolution of Pore Pressure, Stress, and Physical Properties During Sediment Accretion at Subduction Zones. JGR Solid Earth.

Lockhart, L.P., Flemings, P.B., Nikolinakou, M.A., Germaine, J.T., 2023, Velocity-based pore pressure prediction in a basin with late-stage erosion: Delaware Basin, Marine and Petroleum Geology.

Meazell, K.P., Flemings, P.B., 2022, The evolution of seafloor venting from hydrate-sealed gas reservoirs. Earth and Planetary Science Letters.

You, K., Flemings, P.B., Bhandari, A., Heidari, M., Germaine, J.T., 2022, The role of creep in geopressure development. Petroleum Geoscience.


Flemings, P.B, 2021, A Concise Guide to Geopressure: Origin, Prediction, and Applications, Cambridge University Press. Purchase

UT GeoFluids produces innovative concepts and analysis workflows that couple geologic loading and fluid flow to predict pore pressure and stress in the subsurface. These include:

  • UT Centroid: online software to predict reservoir pressure as a function of reservoir geometry and mudstone permeability.
  • Seismic Pressure Prediction Integrated with Geomechanical Modeling: a highly innovative workflow integrating seismic velocity data with geomechanical modeling to predict pressure and the full stress tensor.
  • UT-FAST-P3: An online, educational tool allowing users to predict and compare pore pressure using the full stress tensor while demonstrating why it is important to go beyond vertical effective stress (VES) models.

Learn more.