Oil & Natural Gas Projects
Exploration and Production Technologies
Joint Geophysical Imaging & Logging
The objectives of this research are twofold: First, to investigate the feasibility
of simultaneously inverting different types of geophysical data linked through
a rock physics model to produce a single, self-consistent earth model parameterized
by hydrologic parameters (porosity, fluid, and gas saturations, etc.) rather
than geophysical parameters; second, if such inversion is feasible, to develop
specific algorithms to use surface (land or marine) data and assess these algorithms
in terms of parameter resolution and computational requirements.
Lawrence Berkeley National Laboratory (LBNL)
Sandia National Laboratory
The researchers have developed and demonstrated the first successful joint inversion
algorithms for simultaneously modeling electromagnetic and seismic field data
to produce a single consistent reservoir model of fluid saturations, pressure,
and formation porosity. The work has been presented at several major international
conferences, and a publication on the new algorithms has been accepted for publication
in Geophysics in late 2005 or early 2006.
This research will benefit any effort to quantitatively estimate reservoir parameters
from geophysical data by providing an improved understanding of the complex
interdependence between multiple reservoir parameters and the resulting geophysical
parameters. This project has the potential to provide the first workable joint
geophysical imaging codes to provide direct estimates of reservoir parameters
from geophysical data.
The fundamental problem in geophysical inversion is the underdetermined nature
of the problem. Whether the objective is structural imaging or mapping reservoir
fluid properties, the number of parameters, which control the geophysical response,
is greater than the available degrees of freedom in individual geophysical data
sets (seismic, electromagnetic [EM], gravity, etc.). For example, in 4-D reservoir
monitoring, time-lapse changes in acoustic and elastic impedance are primarily
functions of changes in pressure, water saturation, and gas saturation. Unfortunately,
the changes in the acoustic and elastic (P and S) impedances do not uniquely
map to changes in the reservoir parameters.
However, this ambiguity, or non-uniqueness, can be reduced and sometimes eliminated
by incorporation of other geophysical data sets. In this example, EM data would
provide independent estimates of water saturation changes, thus constraining
the pressure and gas saturation changes estimated from the seismic data. Additional
constraints can be provided by fine-scale geophysical measurements made in boreholes.
The optimum technique for estimating structure and/or reservoir parameters must
be capable of combining all available data in an integrated, self-consistent
model. Self-consistent means that the geophysical parameters (velocity, conductivity,
density) of the model, which fits the observed data, are all linked through
a rock properties model that relates the geophysical parameters to the fluid
parameters of the reservoir.
Accurate estimation of reservoir parameters from geophysical data is of utmost
importance in hydrocarbon exploration and production. The project performers
have developed a new joint inversion algorithm to directly estimate reservoir
parameters using both seismic amplitude versus angle (AVA) and marine controlled-source
electromagnetic (CSEM) data. The reservoir parameters are linked to the geophysical
parameters through a rock-properties model. Errors in the rock-properties model
parameters introduce errors of comparable size in the joint inversion reservoir
parameter estimates. Tests of the concept on synthetic one-dimensional models
demonstrate improved fluid saturation and porosity estimates for joint AVA-CSEM
data inversion (compared with AVA or CSEM inversion alone). Comparing inversions
of AVA, CSEM, and joint AVA-CSEM data over North Sea Troll field-at a location
with well control- shows that the joint inversion produces estimated gas saturation,
oil saturation, and porosity that is closest (as measured by the RMS difference,
L1 norm of the difference, and net over the interval) to the logged values,
whereas CSEM-only inversion provides the closest estimates of water saturation.
In summary, researchers have:
- Demonstrated the first successful joint inversion of marine electromagnetic
and seismic data for the accurate estimation of reservoir fluid saturations.
- Made presentations of results at EAGE and SEG international meetings.
- Submitted and been notified of acceptance of a major publication on the work
by Geophysics magazine for publication in late 2005 or early 2006.
Current Status (June 2006)
The project is reaching the end of DOE funding. Researchers have negotiated new industry funding from ExxonMobil and ConocoPhillips. Other international companies (Norsk Hydro, Statoil) are negotiating to fund research in this area with LBNL.
Project Start: July 1, 2003
Project End: April 10, 2006
Anticipated DOE Contribution: $485,000
Performer Contribution: $400,000 (45% of total)
Other Government Organizations Involved: Sandia National Laboratory
NETL - Purna Halder (firstname.lastname@example.org or 918-699-2083)
LBNL - Mike Hoversten (email@example.com or 510-486-5086)
Hoversten, G.M., Cassassuce, F., Gasperikova E., Newman G.A., , Chen J., Rubin,
Y., Hou, Z., and Vasco D., Direct Reservoir Parameter Estimation Using Joint
Inversion of Marine Seismic AVA & CSEM Data, accepted for publication in
Hoversten, G.M., Milligan, P., Byun, J., Washbourne, J., Knauer, L. C., Harness
P., Crosswell electromagnetic and seismic imaging: An examination of coincident
surveys at a steamflood project, Geophysics, 2003, 69, pp. 406-414.
Hoversten, G. M., Gritto, R., Washbourne, J., Daley, T. M., Pressure and
Fluid Saturation Prediction in a Multicomponent Reservoir, using Combined
Seismic and Electromagnetic Imaging, Geophysics, 2003, 68, pp. 580-1591.
Results of inversion of field data over an oil and gas field in the North
Sea. Inversion for water (left panel), gas (second from left), oil (second
from right), and porosity (right panel), using both seismic AVA and CSEM data.
Red plus signs are log values for comparison, the green line represents parameter
values after first iteration when smoothing has flattened the starting model,
and the blue line depicts final inversion parameters. Black dashed lines are
Data from Troll field were used to demonstrate the CSEM technique.