Simultaneous sourcing during both seismic acquisition and seismic inversion
US-9772413-B2 · Sep 26, 2017 · US
US10422922B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10422922-B2 |
| Application number | US-201314389956-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 15, 2013 |
| Priority date | May 24, 2012 |
| Publication date | Sep 24, 2019 |
| Grant date | Sep 24, 2019 |
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A system and method to predict rock strength by directly inverting for petrophysical properties. In one embodiment, seismic data is received or obtained from a seismic survey (step 101 ). The seismic data are then conditioned (step 103 ) in order to prepare them for an inversion process (step 105 ). The inversion process has an embedded rock physics model that allows the inversion to be formulated based upon, and thereby outputting or calculating (step 107 ), petrophysical properties. Rock strength data may then be calculated from the petrophysical properties (step 109 ).
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What is claimed is: 1. A method comprising: (a) developing an initial subsurface geologic model for M petrophysical properties that indirectly affect the geophysical data, wherein M is at least one; (b) selecting a reflectivity model; (c) selecting a rock physics model that relates the M petrophysical properties to N geophysical properties that directly affect the geophysical data, wherein M<N; (d) simulating, with a computer, synthetic geophysical data using the initial subsurface geologic model, the rock physics model and the reflectivity model, wherein the M petrophysical properties are obtained from the initial subsurface geologic model and substituted into the rock physics model to compute the N geophysical properties required as input to the reflectivity model; (e) comparing, with a computer, the synthetic geophysical data to the measured geophysical data and quantifying a degree of misfit; (f) updating, with a computer, the initial subsurface geologic model to reduce the misfit; (g) computing, with a computer, one or more subsurface rock strength properties, which includes at least static Young's modulus, from the updated subsurface geologic model; (h) generating, with a computer, a subsurface image that includes fracture networks, from the one or more subsurface rock strength properties from the updated subsurface geologic model; and (i) predicting fracability based on the subsurface image that includes fracture networks; and (j) stimulating fractures in earth's subsurface based on the predicted fracability and the subsurface image that includes fracture networks. 2. The method of claim 1 , further comprising repeating (d)-(f) for one or more iterations before performing (g), wherein the updated model from (f) is used to repeat (d). 3. The method of claim 1 , wherein the petrophysical properties include one or more of microcrack density, microcrack orientation distribution, porosity or clay percentage. 4. The method of claim 1 , wherein the geophysical properties include P-wave velocity, S-wave velocity and density. 5. The method of claim 1 , wherein the rock strength properties additionally include Poisson's ratio and density. 6. The method of claim 1 further comprising conditioning at least a portion of the measured geophysical data before performing step (d). 7. The method of claim 1 , wherein the rock physics model treats at least HTI anisotropy. 8. The method of claim 1 , wherein the rock physics model and the reflectivity model are non-linear. 9. The method of claim 1 further comprising acquiring well log and/or core measurement data and calibrating at least one of the subsurface rock strength properties using the well log and/or core measurement data. 10. The method of claim 1 , further comprising: drilling a well into the subsurface formation based at least in part on the at least one subsurface rock strength properties; and producing hydrocarbons from the well. 11. The method of claim 1 , wherein the rock physics model is an anisotropic rock physics model that treats at least HTI anisotropy.
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