Active Noise Injection Computations for Improved Predictability in Oil and Gas Reservoir Characterization and Microseismic Event Analysis

Abstract

Application of nonlinear resonance interferometry is introduced as a new geophysical approach to improve predictability in characterization of subsurface microseismic event analysis and propagation of fracture. In contrast to reflection methods that remove random information noise, nonlinear resonance interferometry exploits the full microseismic acquisition spectrum. In some examples, systems and techniques implement novel computational interactions between acquired microseismic wavefield attributes and a nonlinear system in software to amplify distortions in microseismic noise and exploits injection of synthetic noise, in software format, to fracture events.

1 - 9 . (canceled) 
     
     
         10 . A method comprising:
 obtaining, from microseismic data for a formation of interest, a one-dimensional voxel vector for a voxel from multiple voxels associated with the formation of interest; obtaining spectral data generated from microseismic data from the formation of interest obtained during a known period of no fracturing;   coupling the spectral data with the one dimensional voxel vector to determine whether a resonance event occurs;   when a resonance event occurs, producing an output indicating that the voxel has the attribute of interest; and   when the resonance event does not occur, producing an output indicating that the voxel does not have the attribute of interest.   
     
     
         11 . The method of  claim 10 ,
 wherein the obtaining the one-dimensional voxel vector comprises normalizing amplitudes corresponding to the one dimensional voxel vector to fit within a range.   
     
     
         12 . The method of  claim 10 , wherein obtaining the spectral data comprises:
 obtaining microseismic noise data;   obtaining control voxel data; and   combining the microseismic noise data and the control voxel data using a quantum mechanical model to produce the spectral data.   
     
     
         13 . The method of  claim 12 ,
 wherein obtaining the control voxel data comprises obtaining a control voxel data of a voxel not exhibiting the attribute of interest.   
     
     
         14 . The method of  claim 11 , wherein coupling the spectral data with the one dimensional voxel vector to determine whether a resonance event occurs comprises using a nuclear magnetic resonance (“NMR”) master rate equation to generate quantum stochastic resonance based on the one-dimensional voxel vector, synthetic noise, and the spectral data. 
     
     
         15 . A method comprising,
 obtaining normalized voxel data for a voxel from voxelized microseismic data for a geological subsurface formation;   obtaining normalized control voxel data from microseismic data from a period known not to have significant fracture events;   generating spectral data from the normalized control voxel data;   performing a first non-linear coupling of the voxel data with spectral data to generate a first resonance, wherein the coupling is driven by noise having an intensity within a first cutoff band;   in response to generating the first resonance, adjusting the cutoff band to a second cutoff band, different than the first cutoff band;   performing a second non-linear coupling of the voxel data with the spectral data associated with an attribute of the subsurface formation to generate a second resonance, wherein the second coupling is driven by noise having an intensity within a second cutoff band;   in response to generating the second resonance, generating an indication that the attribute exists in the voxel, wherein the attribute comprises a subsurface fracture; and   in response to the second coupling not producing a second resonance producing an indication that the attribute does not exists in the voxel.   
     
     
         16 . The method of  claim 15 , wherein the first resonance comprises a first quantum stochastic resonance. 
     
     
         17 . The method of  claim 15 , further comprising assembling the voxel data in an attribute volume with the indication that that the attribute exists in the voxel. 
     
     
         18 . The method of  claim 15 :
 wherein the voxelized microseismic data comprises multiple voxels including the voxel; and   further comprising determining the first cutoff band based on a percentage of an average intensity of the multiple voxels.   
     
     
         19 . The method of  claim 15 :
 prior to the first coupling, performing a third coupling of the voxel data with the spectral data associated with an attribute of the subsurface formation to generate a third resonance, wherein the third coupling is driven by noise having an intensity within a third, different cutoff band; and   in response to generating the first resonance, adjusting the third cutoff band to the first cutoff band.