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Combined Borehole Seismic and Electromagnetic Inversion
Project Number

The objectives of the project are to:

  • Demonstrate the feasibility for the joint quantitative inversion of borehole seismic and electromagnetic (EM) measurements, well logs, and core data.
  • Develop the necessary computer algorithmic and software infrastructure to jointly invert borehole seismic and EM data into 3-D spatial distributions of petrophysical properties (e.g., porosity, permeability, permeability anisotropy, and fluid saturations).
  • Evaluate specific configurations for deep-sensing borehole EM and seismic instruments that will provide optimal spatial resolutions and penetration length.
  • Assess the inversion algorithms on synthetic reservoir models constructed from paradigms of highly laminated sands, tight reservoirs, dual-porosity carbonates, and naturally fractured formations. Some of the synthetic reservoir models will be based on actual hydrocarbon reservoir models and data thereof provided to us by Anadarko Petroleum Corporation and Unocal Corporation (now Chevron Corp).

Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA
Anadarko Petroleum Corporation, Oklahoma City, OK
Unocal Corporation (now part of Chevron Corp.), El Segundo, CA
University of Texas, Austin, TX


Several current and recent NGOTP projects have focused on reservoir fluid and lithology prediction from single boreholes, between boreholes, and from surface measurements, including:

  • Development of Single-Well Seismic Imaging Technology, LBNL; project complete.
  • Inversion of Full Waveform Seismic Data for Three-Dimensional Elastic Parameters, Sandia National Laboratory; first year.
  • Integrated Reservoir Monitoring Using Seismic and Crosswell Electromagnetics, LBNL; second year).

These projects have developed state-of-the-art data acquisition and modeling techniques for seismic and EM data.

The Integrated Reservoir Monitoring Using Seismic and Crosswell Electromagnetics project has demonstrated the added spatial resolution that can be gained in saturation prediction by combining seismic and EM data in the interpretation process. Work to date on the combined use of seismic and EM has centered on an iterative, interpreter-driven process of using results from one technique to guide and constrain the interpretation of the other. The next logical step is to develop a rigorous formal linkage between seismic and EM imaging through the mathematics of inversion.

This project has developed a method for combining seismic and EM measurements to predict changes in water saturation, pressure, and carbon dioxide gas/oil ratio in a reservoir undergoing CO2 flooding. The algorithms and methodology are applicable to any oil and gas applications with multiphase-fluid flow.

Crosswell seismic and EM data sets taken before and during CO2 flooding of an oil reservoir were inverted to produce crosswell images of the change in compressional velocity, shear velocity, and electrical conductivity during a CO2 injection pilot study. A rock properties model was developed using measured log porosity, fluid saturations, pressure, temperature, bulk density, sonic velocity, and electrical conductivity. The parameters of the rock properties model are found by an L1-norm simplex minimization of predicted and observed differences in compressional velocity and density. A separate minimization, using Archie’s law, provides parameters for modeling the relationships among water saturation, porosity, and electrical conductivity. The rock-properties model is used to generate relationships between changes in geophysical parameters and changes in reservoir parameters. Electrical conductivity changes are directly mapped to changes in water saturation; estimated changes in water saturation are used, along with the observed changes in shear wave velocity to predict changes in reservoir pressure.

The estimation of the spatial extent and amount of CO2 relies on first removing the effects of the water saturation and pressure changes from the observed compressional velocity changes, producing a residual compressional velocity change. This velocity change is then interpreted in terms of increases in the CO2 /oil ratio. Resulting images of the CO2/oil ratio show CO2-rich zones that are well correlated to the location of injection perforations, with the size of these zones also correlating to the amount of injected CO2. The images produced by this process are better correlated to the location and amount of injected CO2 than are any of the individual images of change in geophysical parameters.

The algorithms developed have been demonstrated to be superior at predicting fluid saturation within a reservoir compared with prior technology. The research and publications from this project have led to the successful developments of the follow-on Natural Gas and Oil Technology Partnership (NGOTP) project, Joint Geophysical Imaging, which has led to over $1,000,000 in direct industry funding for joint seismic and electromagnetic inversion research at LBNL.

Project researchers have:

  • Developed a Bayesian model to estimate categorical rock physics parameters (bulk and shear modulus and density) and their spatial distribution around a borehole, in which rock types and parameters of each type are random variables and 3-D velocity and stress are data.
  • Developed a Markov chain Monte Carlo method (i.e., the Swendsen and Wang algorithm) and tested it for a synthetic case study with two types of rock. The method and algorithm work fine for those problems with only two types of rock.
  • Extended the algorithms from two types of rock to three or more types of rock. The method needs to be tested further using synthetic case studies with three or more types of rock and more data are also needed.
  • Developed a Bayesian model to estimate continuous rock physics parameters, in which unknown variables can take any values within certain ranges, instead of categorical variables.
Current Status

(February 2008)
The original project concluded at the end of 2003; additional funding has continued the research. The result has shown that seismic data could provide information on rock physics parameters

Lawrence Berkeley National Laboratory (LBNL) with the University of Texas, in a DOE Project, has developed state-of-the-art data acquisition and modeling techniques for integration of seismic and Electro-Magnetic (EM) data. The Integrated Reservoir characterization using seismic and cross-well EM data has demonstrated the added resolution in hydrocarbon saturation prediction. The project also involves the development of algorithms and computer codes for the interpretation of borehole seismic and EM measurements. The successful integration of borehole sonic and EM measurements considerably improves the current state-of-the-art technology to detect and assess the hydrocarbon potential of reservoir flow units undetectable with conventional seismic methods. Researchers will continue to validate the results with field data.

This project was funded through DOE’s NGOTP program. The project is a joint contract with the University of Texas at Austin, DE-FC26-04NT15507.

Current Status
The original project concluded at the end of 2003; additional funding continued the research.

Project Start
Project End
DOE Contribution


Performer Contribution


Contact Information

NETL - Purna Halder ( or 918-699-2083)
LBNL - Chen Jinsong ( or 510-486-5686)

Hoversten, G.M., Milligan, P., Byun, J., Washbourne, J., Knauer, L.C., Harness P., 2003, Crosswell electromagnetic and seismic imaging: An examination of coincident surveys at a steamflood project. Geophysics 69, 406- 414 .

Hoversten, G.M., Gritto, R., Washbourne, J., Daley, T.M., 2003, Pressure and Fluid Saturation Prediction in a Multicomponent Reservoir, using Combined Seismic and Electromagnetic Imaging: Geophysics, 68, 1580-1591.

Chen, J. and Hoversten, M., 2003, Joint stochastic inversion of geophysical data for reservoir parameter estimation, 73rd Ann. Internat. Mtg., Society of Exploration Geophysicists, 726-729.

Hoversten, G.M., Gritto, R., Daily, T., Washbourne, J., 2002, Fluid saturation and pressure prediction in a multicomponent reservoir by combined seismic and electromagnetic imaging, SEG Expanded Abstracts, 1770-1773.

Hoversten, G.M., Gritto, R., Kirkendal, B., 2001, Crosswell Seismic and Electromagnetic Monitoring of CO2 Enhanced Oil Recovery, SEG Development & Production Forum, Taos, NM.

Predicted CO2/oil ratio.
Predicted CO2/oil ratio.