| 摘要 |
A system, method and computer program product for generating probabilistic models of a subsurface region of the earth of interest. The system, method can be implemented efficiently to enable real-time imaging of a sub-surface structure. The system, method can provide users with the ability to assess where their subsurface images are reliable and where they are not in order to assist in the selection of low-risk, high-reward sights indicated as having oil potential for drilling. The system, method allows users to estimate a degree of uncertainty to be expected when drilling in a specific location. The knowledge of this uncertainly can be used to guide drilling in real-time to reduce the time to oil (and thereby the cost of drilling), increase the efficiency of drill maintenance and reduce the risk associated with incorrectly identifying the depth at which pressure might spike. |
| 主权项 |
1. A method for creating seismic models of subsurface structures comprising:
collecting survey shot data of a sub-surface area of interest, said area having sub-surface structure; using the collected shot data and one or more seismic modeling algorithms to generate a set of models describing the sub-surface structure of a part or the entire area; for each of said generated models, conducting, in a computer system, a forward modeling simulation of said generated model to generate shot data from the model, the conducting including:
dividing the forward modeling simulation across a plurality of computing nodes, each computing node processing a portion of the forward modeling simulation of the said generated model;combining partial images, which are results of the processing from the plurality of nodes, the combined partial images representing the generated shot data; measuring the error value between the collected survey shot data and the generated shot data from the simulated model; computing, using a programmed processor device, a certainty measure from the error value to assess a confidence degree of the generated model; and further computing an objective function based on the generated model as a function of said collected survey shot data and a set of model parameters, said objective function defined as a set of partial derivative equations; and iteratively solving said set of partial derivative equations to reach an optimal set of model parameters for use in the generated model, and measuring a progress of an optimization process after each iteration according toPk-Pk-1Pk-1>T where k is an index of iterations, and a difference between an immediately past probability measure of a prior iteration, Pk−1 and a current probability measure of a current iteration Pk is compared against a fixed number threshold T, such that if an improvement in probability is greater than T, then adjusting the model parameters, incrementing index k and begin the next iteration; otherwise, if an improvement in probability is less than T, then terminate the modeling process. |
