Yangjun Liu

Application of Steering Filters to Localized Anisotropic Tomography With Well Data

Andrey Bakulin, Marta Woodward*, Yangjun (Kevin) Liu, Olga Zdraveva, Dave Nichols, Konstantin Osypov WesternGeco Summary Estimation of anisotropic parameters for depth models requires some type of joint inversion of seismic and borehole data. We demonstrate that conventional grid reflection tomography can be adapted to simultaneously invert for all parameters of a local 3D anisotropic model. Success requires three key ingredients: jointly invert seismic and well data, localize tomography to a small volume around the borehole, and steer the updates along seismic horizons with steering filters. We describe steering filters and demonstrate 3D anisotropic tomography regularized with steering-filter preconditioners on a synthetic data set.

Anisotropic model building with wells and horizons: Gulf of Mexico case study comparing different approaches

Anisotropic depth imaging with ver-tical transversely isotropic (VTI) models has become the dominant practice in the industry. However, anisotropic parameters for these models continue to be derived by basic practices without the use of tomography. Hanging a single profile of Thomsens parameters from the water bottom still remains the most common practice. In a simple structural setting, it is usually possible to focus the data and obtain a good image despite having a simple and unrealistic model for Thomsens parameters. However, depth positioning of such images is usually suboptimal. Better positioning requires more geologically plausible models. In addition, imaging in complex settings may require tilted transversely isotropic (TTI) models.

From Quantifying Seismic Uncertainty to Assessing E&P Risks And the Value of Information

Accurate well placement in oil and gas exploration and production (E&P) requires accurate positioning of interpreted geological structure in the depth domain. In the past decade, with the advancement of sensor and computer hardware technology, the seismic industry has made great improvements in the data acquisition designs as well as depth imaging and model building algorithms. However, the cost/benefit justification for the value of information (VOI) obtained by utilization of these technologies remains mainly to be qualitative. This paper discusses how seismic uncertainty analysis can lead to quantifying the VOI and technical risks associated with E&P projects.

Anisotropic Model Building With Wells And Horizons: Gulf of Mexico Case Study Comparing Different Approaches

Anisotropic depth imaging with Vertical Transversely Isotropic (VTI) models has become dominant in the industry. However, anisotropic parameters for these models continue to be derived by very basic practices without use of tomography. Hanging a single profile of Thomsen parameters from the water bottom still remains the most common practice. In a simple structural setting, it is usually possible to focus the data and obtain a good image despite having a simple and unrealistic model for Thomsen parameters. However, depth positioning of such images is usually suboptimal. Better positioning requires more geologically plausible models. In addition, imaging in complex settings may require Tilted Transversely Isotropic (TTI) models. In this case study we construct several anisotropic models using approaches with increasing complexity and evaluate the model impact on image quality and ties to well data. We start with a “new default” model, where a single, smoothed, borehole-calibrated profile is hung from the water bottom, and then we progress to an “intermediate” model where a similar profile with more vertical details is propagated using major geological horizons. We finish with an “elaborate” model, where profiles from several wells are interpolated throughout the model using geologic horizons. We contrast all these models to an “old default” model derived without well calibration. We observe a generally steady improvement in well ties compared to the “old default” model, with the proportionally largest change coming from simple well calibration (“new default” model) and additional uplift coming from incorporating geologic horizons (“intermediate” model). Differences between “intermediate” and “elaborate” models are small, while switching to TTI models clearly helps resolve complex structures in dipping areas.

Application of the Rock Physics Model in Anisotropic Seismic Velocity Model Building and Quantitative Reservoir Structural Uncertainty Analysis: Gulf of Mexico Case Study

Accurate anisotropic seismic velocity model building is the key to the success of seismic depth imaging projects in complex geological settings. Tomography has been an industry standard velocity model building tool for decades, but simultaneously solving for P-wave velocity, epsilon, and delta with surface seismic data only is an underdetermined inverse problem and unstable. The ambiguity in seismic migration velocity model leads to structural uncertainty in seismic image and is carried over to uncertainty in reservoir modeling. In this paper, we introduce a new method using rock physics compaction modeling of sandy shales to constrain the anisotropic tomography. An effective-media rock model was calibrated with well data for sedimentary basin and was used to build initial vertical transverse isotropy (VTI) velocity models. By running a stochastic simulation of the rock physics model, covariance functions were extracted from possible combination of to P-wave velocity, epsilon, and delta as a priori information to constrain the following anisotropic tomography updates and uncertainty analysis. The case study area is in the Green Canyon in the Gulf of Mexico. The results show that we can successfully constrain three parameters of tomography with the prior information from rock physics. We also performed seismic uncertainty analysis to assess the non-uniqueness of the tomography solutions. 500 velocity models with equivalent residual move out were generated and used to map migrate the reservoir structures. The gross rock volume P10, P50 and P90 were calculated from these 500 realizations to demonstrate the reduction of uncertainty from the rock physics constraints.

Simultaneous Anisotropic Tomography with Rock Physics Constraints - Gulf of Mexico Example

Simultaneously solving for velocity, epsilon, and delta in anisotropic tomography is very challenge. Surface seismic data only is not sufficient for this joint problem. In this work, a model covariance function was built using rock physics to constrain the joint anisotropic tomography. An example from Gulf of Mexico was presented to demonstrate the effectiveness of the method.

Localized anisotropic tomography with checkshot : Gulf of Mexico case study

Borehole information must be used to build accurate anisotropic depth models. While various techniques exist, almost none of them is extendable to a general case of complex structure and deviated wells. Localized tomographic inversion is a flexible approach that can potentially be applied to most complex cases. It attempts to streamline and automate the estimation process by directly incorporating the available well data into conventional reflection tomography. We present a case study from Gulf of Mexico where we invert for local vertically transversely isotropic (VTI) model using a joint dataset consisting of seismic and checkshot data. Because this area has flatlayered structure, the results can be compared with more traditional manual 1D layer-stripping inversion. We invert for three VTI parameters and search for a smooth velocity field that both fits the checkshot traveltimes and flattens all seismic gathers. To regularize tomographic inversion, we apply smoothing operators that are oriented along geological dip and have large lateral extent. The anisotropic profiles derived by tomography and 1D inversion have similar trends, but differ in high-frequency details. Borehole data require careful conditioning before joint inversion because of potential difference in water velocity between seismic and well surveys. The workflow we present can be applied to calibrating anisotropic parameters in the more general case of 3D models with structural dip and borehole data from deviated wells.