Velocity Model-Building For 3D Depth Imaging In The 21st Century
Authors: Fagin Stuart , Randall Richard 
Published: October 2008

Introduction

3D prestack depth imaging has greatly expanded our ability to see geologically complex and subtle reservoirs. However, the application of this technology has been limited by the extensive geophysical analysis, and consequent heightened expense, of projects. Until recently, large 3D prestack depth imaging projects, of the order of 100 square miles of output area, require several months of geophysical analysis time to complete. A large portion of this geophysical analysis time is devoted to the construction of highly accurate velocity models which are pre-requisites for successful depth imaging. Several advancements are on the horizon, with respect to this velocitymodel-building task, which will greatly reduce analysis time to the point where these projects will take weeks rather than months. Two particularly important advancements are discussed here: 3D tomography, and the new solids-based model building systems.

3D tomography

3D tomographic analysis is the newest advance in depth imaging velocity refmement techniques. These techniques refine the velocity model after consideration of the errors (known as residual moveout) produced by the existing model. Tomographic techniques perform this task far more efficiently and effectively than the one-dimensional techniques they are replacing. Indeed, for the past few years, tomographic techniques have been very successfully applied to 2D depth imaging projects. The key technical advantage of tomographic techniques is that they are able to infer appropriate velocity changes in a model, in areas laterally separated from the error observation. For example, based on the residual moveout observed at Trace 100, tomographic analysis may indicate that the velocity at Trace 200 is too slow. These inferences are possible, in tomographic analysis, because these errors are considered in the context of a structured subsurface model through which the traveltime consequences of residual moveout may be evaluated. In contrast, one-dimensional techniques can only infer velocity changes at the same location where the error is observed. This limitation exists because these errors, for the sake of computationally simplicity, are considered in the context of an unstructured subsurface model. This key technical advantage of tomography leads to several strong operational benefits:faster convergence upon anoptimal model with fewer iterations;a far more accurate velocity field; particularly where velocity changes occur rapidly in a lateral direction, andbecause of the accurate velocity field, better depth images.

Unfortunately, until recently, tomography has only been available as a 2D process. For 3D depth imaging, the velocity model-builder has had to rely on the one-dimensional process, with numerous attendant iterations, or using 2D tomography in a serial manner; a somewhat cumbersome process. 3D tomography has emerged as a new technology in the past year and has transformed the speed with which depth imaging projects can be completed. Instead of performing 7 or more iterations, each of which may take several weeks, projects can be completed in 3 or 4 iterations each of which take only one week. A salt diapir from the transition zone of Louisiana is used to illustrate 3D tomography. In Figure I, a standard poststack time image, the base-of-salt and salt flank are poorly imaged.