The project goals are to:
Lawrence Berkeley National Laboratory, Berkeley, CA
Colorado School of Mines, Golden, CO
University of California at Berkeley, Berkeley, CA
Chevron Corp., San Ramon CA
This project is a collaboration among CSM (laboratory experiments), LBNL (theoretical and numerical model development), Cal-Berkeley (seismic forward modeling), and Chevron (providing field data for Q analysis).
Heterogeneity of the elastic properties of rocks at the scale of millimeter-to-centimeter (so-called “mesoscopic scales”) is responsible for a highly variable fluid pressure response across these same scales when the rock is squeezed by a seismic wave. The subsequent fluid flow due to such wave-induced fluid pressure gradients provides significant amounts of seismic attenuation.
The project has resulted in the development of highly efficient poroelastic finite-difference modeling codes that allow the mesoscopic-scale fluid flow induced inside of a rock by a passing wave to be numerically determined. Researchers then calculate the attenuation (1/Q) and seismic velocity for a given synthetic rock sample. This has led to significant insight both into the mechanism responsible for seismic attenuation and into what new information measuring attenuation can bring.
Among many results so far obtained, the project performers have demonstrated that when the mesoscopic heterogeneity is distributed as a self-affine fractal having a Hurst exponent b, the attenuation as a function of frequency f follows the power law Q(f) = f b.
The most important question this project asks is: What is the benefit of obtaining seismic Q from seismic data? To answer this question, one must have a physical model that adequately explains the data. Project results after 10 months of modeling seem to indicate that wave-induced fluid flow over mesoscopic-length scales is the mechanism that shows the most promise. This model will allow researchers to answer the question of what information is in Q. A key step will be next year, when the model predictions are compared directly with data measurements occurring at CSM. At just 10 months into the project, the project performers do not want to answer the posed question until more research has been performed.
Approaching the end of this first year of effort, the LBNL theoretical and numerical modeling has advanced as it should have.
The project is in the second of a 3-year funding effort with the subcontract job for CSM.
This project is a subcontract to DOE project number DE-FC26-04NT15505. The project is not funded in FY 07