This thesis describes new interferometric imaging methods for migration and waveform
inversion. The key idea is to use reflection events from a known reference reflector
to ”naturally redatum” the receivers and sources to the reference reflector.
Here, ”natural redatuming” is a data-driven process where the redatuming Green’s
functions are obtained from the data. Interferometric imaging eliminates the statics
associated with the noisy overburden above the reference reflector.
To mitigate the defocussing caused by overburden errors I first propose the use
of interferometric least-squares migration (ILSM) to estimate the migration image.
Here, a known reflector is used as the reference interface for ILSM, and the data
are naturally redatumed to this reference interface before imaging. Numerical results
on synthetic and field data show that ILSM can significantly reduce the defocussing
artifacts in the migration image.
Next, I develop a waveform tomography approach for inverting the velocity model
by mitigating the velocity errors in the overburden. Unresolved velocity errors in the
overburden velocity model can cause conventional full-waveform inversion to get stuck
in a local minimum. To resolve this problem, I present interferometric full-waveform
inversion (IFWI), where conventional waveform tomography is reformulated so a velocity
model is found that minimizes the objective function with an interferometric
crosscorrelogram misfit. Numerical examples show that IFWI, compared to FWI,
computes a significantly more accurate velocity model in the presence of a nearsurface
with unknown velocity anomalies.
I use IFWI and ILSM for 4D imaging where seismic data are recorded at different
times over the same reservoir. To eliminate the time-varying effects of the near
surface both data sets are virtually redatumed to a common reference interface before
migration. This largely eliminates the overburden-induced statics errors in both data
sets. Results with synthetic and field data show that ILSM and IFWI can suppress
the artifacts caused by non-repeatability in time-lapse surveys. This can lead to a
much more accurate characterization of the movement of fluids over time. In turn,
this information can be used to optimize the extraction of resources in enhanced oil
recovery (EOR) operations.
| Identifer | oai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/627679 |
| Date | 03 1900 |
| Creators | Sinha, Mrinal |
| Contributors | Schuster, Gerard T., Physical Science and Engineering (PSE) Division, Wu, Ying, Peter, Daniel, Vesnaver, Aldo |
| Source Sets | King Abdullah University of Science and Technology |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
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