Jerome R. Krebs

Fast full-wavefield seismic inversion using encoded sources

Full-wavefield seismic inversion (FWI) estimates a subsurface elastic model by iteratively minimizing the difference between observed and simulated data. This process is extremely computationally intensive, with a cost comparable to at least hundreds of prestack reverse-time depth migrations. When FWI is applied using explicit time-domain or frequency-domain iterative-solver-based methods, the seismic simulations are performed for each seismic-source configuration individually. Therefore, the cost of FWI is proportional to the number of sources. We have found that the cost of FWI for fixed-spread data can be significantly reduced by applying it to data formed by encoding and summing data from individual sources. The encoding step forms a single gather from many input source gathers. This gather represents data that would have been acquired from a spatially distributed set of sources operating simultaneously with different source signatures. The computational cost of FWI using encoded simultaneous-source gathers is reduced by a factor roughly equal to the number of sources. Further, this efficiency is gained without significantly reducing the accuracy of the final inverted model. The efficiency gain depends on subsurface complexity and seismic-acquisition parameters. There is potential for even larger improvements of processing speed.

Integrated velocity model estimation for improved positioning with anisotropic PSDM

There are many geologic settings where anisotropic migration is necessary to obtain accurate seismic images. While this is well known, stable anisotropic parameter estimation has posed a serious challenge. Seismic data, though extensive in coverage, cannot constrain the anisotropy parameters alone (Tsvankin and Thomsen, 1995). The set of parameters is better constrained by integrating the seismic information with certain types of well data. However, the well data are generally sparse, so the parameters are only constrained at a few locations. Nonuniqueness is obviously a fundamental issue in our estimation problem.

Fast Full Wave Seismic Inversion Using Source Encoding

Full Wavefield Seismic Inversion (FWI) estimates a subsurface elastic model by iteratively minimizing the difference between observed and simulated data. This process is extremely compute intensive, with a cost on the order of at least hundreds of prestack reverse time migrations. For time-domain and Krylov-based frequency-domain FWI, the cost of FWI is proportional to the number of seismic sources inverted. We have found that the cost of FWI can be significantly reduced by applying it to data processed by encoding and summing individual source gathers, and by changing the encoding functions between iterations. The encoding step forms a single gather from many input source gathers. This gather represents data that would have been acquired from a spatially distributed set of sources operating simultaneously with different source signatures. We demonstrate, using synthetic data, significant cost reduction by applying FWI to encoded simultaneous-source data.

Integrated Velocity Model Estimation For Accurate Imaging

Surface seismic reflections, surface seismic direct arrivals, well data and prior geologic information can be used to constrain a subsurface velocity model.

Three‐dimensional migration of swath surveys

A three‐dimensional (3-D) wave‐equation migration program is used to migrate swath data (swath data are here defined as a very narrow 3-D survey consisting of approximately ten seismic lines and having a width of about 500 m). Three‐dimensionally migrated swath data give an accurate 3-D image of the subsurface and have a higher signal‐to‐noise ratio than 2-D data. These advantages are gained at the expense of lateral resolution in the crossline direction and less extensive 3-D subsurface coverage. Since swaths are on the order of one‐tenth the size of a normal 3-D survey, the costs of gathering and processing swath data are about 10 percent those of a conventional 3-D survey. Thus 3-D migrated swath surveys are a practical means of producing 3-D images in areas where the expense of conventional 3-D surveys is not justified. Following 3-D wave‐equation migration, inlines from the swath data are geologically interpretable. However, crosslines from the swath data are dominated by migration artifacts (often c...

Mapping indentations on salt flanks: A two‐dimensional model study

The salt proximity survey is a common borehole seismic technique designed to locate the salt flank. For such a survey, energy from a seismic source located above the salt body passes through the salt and into receivers located in a well adjacent to the body. Given knowledge of the salt and sediment velocities, the traveltimes of the direct arrivals from this survey can be used to determine the location of the salt flank. Techniques for processing the survey data include the conventional aplanatic mapping method and the ray-tracing method. Historically, both of these methods use first-arrival times to calculate the salt flank location. The authors have collected two-dimensional seismic data from an acoustic model to study the effectiveness of the aplanatic method. They found that the technique failed to map indentations on the salt flank when traveltimes of second and later arrivals were not included in the processing. This would also be true for the ray-tracing method. This failure can be overcome if later arrivals are included in data analysis or, if the data are processed with a wave equation-based program.

Integrated velocity model estimation for accurate imaging

Surface seismic reflections, surface seismic direct arrivals, well data and prior geologic information can be used to constrain a subsurface velocity model. These various sources of subsurface velocity information have different strengths and weaknesses. Integrating all available velocity information into a velocity model increases the accuracy of the model by offsetting the weakness of one data type with the strengths of another. We call the process of building a model that integrates all data integrated velocity model estimation.