Exxonmobil Upstream Research Company

Other

Christopher J DiCaprio

Rebecca L Saltzer

Anoop A Mullur

Garrett M Leahy

Charlie Jing

Jan Schmedes

Method for estimating porosity and water saturation or other geological parameters of a subsurface region when the lithology of the region is unknown, requiring only geophysical data from remote surveys. The geophysical data are inverted (-) treating lithology as a third, and discrete, unknown model parameter () to be solved for in the inversion. A technique for solving mixed integer non-linear programs may be used. Suitable rock physics relationships () are used to relate the desired geological parameters to the geophysical model parameters required for simulating the geophysical data in the inversion process.

Inverting geophysical data for geological parameters or lithology

Method for estimating geological properties in a subsurface region using multiple types of geophysical data (). An initial physical properties modelis constructed. Some parameters in the model are frozen () and optionally portions of the model wave number and spatial domains () and the data frequency and data time domains (), are also frozen. Then, a joint inversion () of the multiple data types is performed to calculate an update to the model only for the portions that are not frozen. The converged model () for this inversion is used as a new starting model, and the process is repeated (), possibly several times, unfreezing more parameters and data each time until the desired spatial and parameter resolution () has been achieved.

Domain freezing in joint inversion

Method for adaptive weighting of geophysical data types in iterative joint inversion to speed convergence and aid escape from local minima of the penalty (objective) function. Two or more geophysical data sets () representing a region of interest are obtained, and are jointly inverted to infer models of the physical properties that affect the particular types of data used. The misfit for each data type is a weighted tem in the penalty function (). The invention involves changing the weights () as the iteration cycles progress when the iteration convergence criteria are satisfied (), to see if they remain satisfied () with the modified penalty function.

Adaptive weighting of geophysical data types in joint inversion

Method for joint inversion of geophysical data to obtain 3-D models of geological parameters for subsurface regions of unknown lithology. Two or more data sets of independent geophysical data types are obtained, e.g. seismic and electromagnetic. Then they are jointly inverted, using structural coupling, to infer geophysical parameter volumes, e.g. acoustic velocity and resistivity. Regions of common lithology are next identified based on similar combinations of geophysical parameters. Then a joint inversion of the multiple data types is performed in which rock physics relations vary spatially in accordance with the now-known lithology, and 3-D models of geological properties such as shale content and fracture density are inferred. The computational grid for the last inversion may be defined by the lithology regions, resulting in average geological properties over such regions, which may then be perturbed to determine uncertainty in lithologic boundaries.

Joint inversion with unknown lithology

Method for estimating a model of seismic velocity in a subsurface region from seismic data () recorded on 3-component instruments. The method measures the apparent incidence angle () of a seismic wave observed at a surface as a function of wave frequency. This apparent angle is converted to an effective velocity as a function of frequency (), which is then inverted () to obtain a subsurface velocity model.

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Houston, TX, United States of America

Christopher J DiCaprio