Nonlinear Inverse Problems: Depth Imaging Challenges
Sunjay S. Sunjay
GEOPHYSICS, BHU, Varanasi, India
Imaging of subsurface is a nonlinear inverse problem.The key challenge that the oil industry must face for hydrocarbon exploration requires the development of state-of-the-art technologies to image subsurface precisely and reconstitute the three-dimensional structure of the Earth. The use of seismic reflections is one of these essential and strategic methods. Reflection imaging is key to seismic exploration because it is used as the basis on which the geoscientists leave no stone unturned to enhance R/P ratio, i.e, quest of new giant oil & gas reservoirs. Seismic Depth imaging and High performance computing are both key components of this revolution. Indeed the fast evolution of computers has enabled the development of specialized algorithms allowing the processing of increasingly large volumes of data generated by seismic acquisitions.
Depth imaging processing is an inverse problem. The objective is to reconstruct one velocity model representation of the sub-surface explaining the seismic input data. The development of these different technologies has followed very closely the progress in high performance computing. The massively parallel intrinsic nature of seismic data allows the geophysicist to develop very efficient algorithms. Parallelism can be applied on individual seismic traces, trace collections (e.g. shot gathers), or frequency planes when frequency domain methods are used. The last decade has seen successively the introduction of the full 3D Kirchhoff Pre-SDM, 3D SHOT profile PSDM based on more expensive approximations of the wave equation and more recently 3D Reverse Time Migration based on a full finite-difference solution of the acoustic wave equation. Quantum computing is the new avenue for supercomputing performance of seismic data of complex geological structures.
Presentation GEO India Expo XXI, Noida, New Delhi, India 2008©AAPG Search and Discovery