Today, seismic tomography is one of the main tools for obtaining a depth-velocity subsurface macro model. Its result largely determines the structural component of the resulting field model, which forms the basis for reserves calculation. It also significantly affects the emerging risks associated with the economic profitability of field development. To reduce these risks, we need to analyze the main sources of uncertainty that arise in the course of all our calculations.
The estimation of the field geometry is based on information about the structural surfaces of horizons extracted from seismic cubes after migration. But mainly it is determined by the depth velocity model that was used during migration. Unfortunately, the mathematical problem that has to be solved to obtain the model parameters is incorrect. This causes the existence of a set of models that satisfy the input data with acceptable accuracy. However, tomography is a deterministic procedure that eliminates non-uniqueness by applying various regularization methods, which makes it impossible to assess the reliability of the obtained results. The problem of estimating the uncertainty of the depth velocity model and, consequently, of the estimated reservoir geometry is not trivial.
To solve this problem, the Seismotech company developed the technology of multivariate tomography. This technology extends the technology of depth velocity model building by calculating the set of acceptable model realizations. The variation of model realizations is determined by the quality of the input data and the smoothness parameters of the inversion algorithm. The proposed method is based on the usage of the stochastic means tool during tomography input data extraction and the stochastic variation of tomography smoothness parameters. The technology allows extracting quantitative characteristics of possible errors and their spatial distribution. The proposed method makes it possible to assess the reliability of the reservoir geometry extracted from seismic images, which allows reducing the risks of making further decisions on the development of oil and gas fields.
*This solution is represented as a standalone module, integrated into the Prime software, it is licensed separately.