Saleh M. Al-Saleh

Improving explicit seismic depth migration with a stabilizing Wiener filter and spatial resampling

We present a new approach to the design and implementation of explicit wavefield extrapolation for seismic depth migration in the space-frequency domain. Instability of the wavefield extrapolation operator is addressed by splitting the operator into two parts, one to control phase accuracy and a second to improve stability. The first partial operator is simply a windowed version of the exact operator for a half step. The second partial operator is designed, using the Wiener filter method, as a band-limited, least-squares inverse of the first. The final wavefield extrapolation operator for a full step is formed as a convolution of the first partial operator with the complex conjugate of the second. This resulting wavefield extrapolation operator can be designed to have any desired length and is generally more stable and more accurate than a simple windowed operator of similar length. Additional stability is gained by reducing the amount of evanescent filtering and by spatially downsampling the lower tempor...

Optimizing the FOCI algorithm with a weighted least-squares approach

Summary Recursive wavefield extrapolation methods can effectively handle lateral velocity variations, but require short stable operators to be computationally efficient. The forward operator and conjugate inverse (FOCI) algorithm can be used to design sufficiently stable wavefield extrapolators. However, the FOCI algorithm generally requires long operators to generate good images. In this paper we present an enhanced FOCI algorithm that uses weighted leastsquares. With the optimized algorithm it is possible to design operators as short as 9 points that can remain practically stable in a recursive scheme. Zero-offset migration impulse responses and images from prestack depth migrations of the Marmousi dataset are used to compare the effects of these enhancements to results from the original algorithm.

Explicit wavefield extrapolation directly from topography

Summary Downward continuation methods assume that extrapolation takes place between two planes, but most land surveys are acquired over irregular surfaces. Most approaches that allow downward continuation methods to handle such data, like the wave equation datuming and zero-velocity layer methods, require some processing prior to migration. In this paper, we show how explicit wavefield extrapolation methods in the space-frequency domain can efficiently extrapolate data directly from rugged topography. By building operators with different depth steps, these wavefield extrapolators can handle lateral velocity and topographic variations. We use a source-receiver migration technique to illustrate how this approach can be implemented, using a synthetic dataset as an example.

Optimizing explicit depth migration with a stabilizing Wiener filter and spatial resampling

We present a new approach to the design of stable and accurate wavefield extrapolation operators needed for explicit depth migration. We split the theoretical operator into two component operators, one a forward operator that controls the phase accuracy and the other an inverse operator, designed as a Wiener filter that stabilizes the first operator. Both component operators are designed to have a specific fixed length and the final operator is formed as the convolution of the components. We utilize this operator design method to build an explicit, wavefield extrapolation method based on the migration of individual source records. Two other features of our method are the use of dual operator tables, with high and low levels of evanescent filtering, and frequency-dependent spatial down sampling. Both of these features improve the accuracy and efficiency of the overall method. Empirical testing shows that our method has a similar performance to the time-migration method called phase shift, meaning it scales as NlogN. We illustrate the method with tests on the Marmousi synthetic dataset. We call our method FOCI which is an acronym for forward operator conjugate inverse.

The big rush to the Middle East unconventional reservoirs

North Americas great success in unlocking unconventional reservoirs has inspired many oil companies in the Middle East to focus on and develop their large unconventional endowment. To engage with the oil and gas industry in the region, SEG Middle East organized a technology workshop, “The Role of Geophysics in Unlocking Unconventional Reservoirs,” which was held in Dubai, UAE, 18–20 November 2013. The workshop attracted more than 90 professionals from national and international oil companies as well as service providers. The large number of participants indicates the enormous interest in understanding unconventional reservoirs, not only as a new challenge but also for the opportunities that come with it.

Model‐based noise suppression using nonstationary filters

Surface waves can have complicated wave paths when propagating through a complex near surface. Removing this dispersive energy is an important step to focus the subsurface seismic image. Model-based downward continuation techniques offer one solution to this problem but are computationally expensive. They require downward continuing the wavefield through the surface wave propagation zone followed by forward modeling back to the recording surface. These downward continuation techniques also require sorting the data between the shot and receiver domains for each extrapolation.

The FOCI method versus the WLSQ and Hale's wavefield extrapolation methods

Recursive wavefield extrapolation methods are more powerful than ray theory based methods because of their greater ability to handle strong lateral velocity variations. Wavefield extrapolation methods have two major problems: (1) the extrapolator instability and (2) the computational expense. The forward operator and conjugate inverse (FOCI) method is an appropriate method for designing accurate and efficient extrapolation operators that remain stable in a recursive algorithm. FOCI’s results are comparable with results obtained with other known methods such as Hale’s and the weighted least square (WLSQ) extrapolation methods. Further, the spatial resampling in the FOCI method offers computational advantages.