A new paper is added to the collection of reproducible documents: Missing log data interpolation and semiautomatic seismic well ties using data matching techniques
Relating well log data, measured in depth, to seismic data, measured in time, typically requires estimating well log impedance and a time-to-depth relationship using available sonic and density logs. When sonic and density logs are not available, it is challenging to incorporate wells into integrated reservoir studies as the wells cannot be tied to seismic. We propose a workflow to estimate missing well log information, automatically tie wells to seismic data and generate a global well-log property volume using data matching techniques. We first use local similarity scan to align all logs to constant geologic time and interpolate missing well log information. Local similarity is then used to tie available wells with seismic data. Finally, log data from each well is interpolated along local seismic structures to generate global log property volumes. We use blind well tests to verify the accuracy of well-log interpolation and seismic-well ties. Applying the proposed workflow to a 3D seismic dataset with 26 wells achieves consistent and verifiably accurate results.
A new paper is added to the collection of reproducible documents: Seismic data interpolation using generalised velocity-dependent seislet transform
Data interpolation is an important step for seismic data analysis because many processing tasks, such as multiple attenuation and migration, are based on regularly sampled seismic data. Failed interpolations may introduce artifacts and eventually lead to inaccurate final processing results. In this paper, we generalize seismic data interpolation as a basis pursuit problem and propose an iteration framework for recovering missing data. The method is based on nonlinear iteration and sparse transform. A modified Bregman iteration is used for solving the constrained minimization problem based on compressed sensing. The new iterative strategy guarantees fast convergence by using a fixed threshold value. We also propose a generalized velocity-dependent (VD) formulation of the seislet transform as an effective sparse transform, in which the nonhyperbolic normal moveout equation serves as a bridge between local slope patterns and moveout parameters in the common-midpoint domain. It can also be reduced to the traditional VD-seislet if special heterogeneity parameter is selected. The generalized VD-seislet transform predicts prestack reflection data in offset coordinates, which provides a high compression of reflection events. The method was applied to synthetic and field data examples and the results show that the generalized VD-seislet transform can reconstruct missing data with the help of the modified Bregman iteration even for nonhyperbolic reflections under complex conditions, such as VTI media or aliasing.
A new paper is added to the collection of reproducible documents: Predictive painting across faults
Predictive painting can effectively spread information in 3D volumes following the local structures (dips) of seismic events. However, it has troubles spreading information across faults with significant displacement. To address this problem, we propose to incorporate fault slip information into predictive painting to correctly spread information across faults. The fault slip is obtained by using a local similarity scan to measure local shifts of the different sides of a fault. We propose three different methods to utilize the fault slip information: 1) area partition method, which uses fault slip to correct the painting result after predictive painting in each divided area; 2) fault-zone replacement method, which replaces fault zones with smooth transitions calculated with the fault slip information to avoid sharp jumps; and 3) unfaulting method, where we use the fault slip information to unfault the volume, perform predictive painting in the unfaulted domain, and then map the painting result back to the original space. The proposed methods are tested in application of predictive painting to horizon picking. Numerical examples demonstrate that predictive painting after incorporating fault slip information can correctly spread information across faults, which makes the proposed three approaches of utilizing fault slip information effective and applicable.