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Horizontal Stress Magnitude Prediction

IP.com Disclosure Number: IPCOM000237696D
Publication Date: 2014-Jul-02

Publishing Venue

The IP.com Prior Art Database

Abstract

The invention is a novel method to predict horizontal stress magnitudes in the subsurface. The challenge is that present-day stresses are a snapshot in the context of evolving geologic processes, and that present-day measurements cannot account for the history of a formation, in particular for viscous deformation during burial. The invention combines log-based information from which stress variations with depth can be inferred with stress trend information that encompasses stress history information, and calibrates the predicted horizontal stress magnitude with a data point of measured horizontal stress magnitude and corresponding depth. A detailed description of the invention is provided in the attachments: "Horizontal stress modeling - Text.pdf" and "Horizontal stress modeling - Figures.pdf". A short description: Our method is able to predict effective horizontal stress magnitudes from the following input that is typically available in field applications: a profile of effective vertical stress magnitudes, a data point of effective horizontal stress magnitude and corresponding depth, and a profile of the estimated effective stress ratio. We note that the product of effective stress ratio and effective vertical stress magnitude should deliver the effective horizontal stress magnitude for a zero-lateral strain case with constant, perfectly linear elastic materials. However, typically the behavior of subsurface formations cannot be accurately described this way. Our new method therefore considers the product of estimated effective stress ratio and effective vertical stress magnitude as a base function, and analyzes its trend and perturbations. Using trend and perturbations the method uses a weight function to compute a non-dimensional shape function that reflects the appropriate shape of the horizontal stress magnitude profile. The weight function used in the present work depends on the profile of vertical stress magnitude, but is not so limited and may also be tied to material properties that can be derived from logging data, or obtained otherwise, or estimated. The shape function is calibrated using the data point of effective horizontal stress magnitude and corresponding depth to obtain the final prediction of horizontal stress magnitude The advantage of the invention over existing methods is that it does not use a large number of free parameters ('fudge factors') or empirical relations Our method can readily be extended to use a plurality of data points of effective horizontal stress magnitude and corresponding depth. In one embodiment of such an extension one would use distance-weighted averaging over individual stress predictions. In one embodiment more than one data point can be used together in this method. We note that the above only describes one embodiment of our new method, and that another embodiment exists that may use other characteristics of the base function and its elements (effective stress ratio and vertical stress magnitude profile), or other techniques to assemble the shape function. Another embodiment may use this technique without following each of the described steps and compute the prediction in fewer or more steps. Another embodiment will achieve the mathematically equivalent operations by executing mathematical operations in a different order. Another embodiment will achieve the mathematically equivalent operations by executing mathematical operations not specified here. Another embodiment does not use the effective stress ratio as input, but material properties derived from logging data or obtained or estimated otherwise We plan to test the prediction accuracy of the invention with more numerical cases and with field data, to compare it with existing prediction methods, and to build an employable commercial product.

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Horizontal Stress Magnitude Prediction

The invention is a novel method to predict horizontal stress magnitudes in the subsurface. The challenge is that present-day stresses are a snapshot in the context of evolving geologic processes, and that present-day measurements cannot account for the history of a formation, in particular for viscous deformation during burial. The invention combines log-based information from which stress variations with depth can be inferred with stress trend information that encompasses stress history information, and calibrates the predicted horizontal stress magnitude with a data point of measured horizontal stress magnitude and corresponding depth.

A detailed description of the invention is provided in the attachments: "Horizontal stress modeling - Text.pdf" and "Horizontal stress modeling - Figures.pdf". A short description: Our method is able to predict effective horizontal stress magnitudes from the following input that is typically available in field applications: a profile of effective vertical stress magnitudes, a data point of effective horizontal stress magnitude and corresponding depth, and a profile of the estimated effective stress ratio. We note that the product of effective stress ratio and effective vertical stress magnitude should deliver the effective horizontal stress magnitude for a zero-lateral strain case with constant, perfectly linear elastic materials. However, typically the behavior of subsurface formations cannot be accurately described this way. Our new method therefore considers the product of estimated effective stress ratio and effective vertical stress magnitude as a base function, and analyzes its trend and perturbations. Using trend and perturbations the method uses a weight function to compute a non-dimensional shape function that reflects the appropriate shape of the horizontal stress magnitude profile. The weight function used in the present work depends on the profile of vertical stress magnitude, but is not so limited and may also be tied to material properties that can be derived from logging data, or obtained otherwise, or estimated. The shape function is calibrated using the data point of effective horizontal stress magnitude and corresponding depth to obtain the final p...