Method For Combining Seismic Data Sets

Abstract

A method is disclosed for combining seismic data sets. This method has application in merging data sets of different vintages, merging data sets collected using different acquisition technologies, and merging data sets acquired using different types of sensors, for example merging hydrophone and geophone measurements in ocean bottom seismic data. In one embodiment, a desired data trace is to be determined from a set of measured data traces, and the following steps are applied: (a) model filters are constructed which express the deterministic relationship between the desired data trace and each available measured trace that depends on the desired data trace; (b) the noise properties associated with each measured data trace are determined; (c) a sufficient statistic for the desired data trace is formed by application of an appropriate filter to each measured trace and summing the filter outputs; (d) the sufficient statistic is further processed by a single-input single-output estimator to construct an estimate of the desired data trace from the sufficient statistic.

1 . A method for combining at least two seismic data sets comprising:
 a) determining model filters relating at least two measured data elements from said seismic data sets to a desired data element;   b) determining at least one noise characteristic for the measured data elements;   c) forming a sufficient statistic for the desired data element from the measured data elements based on at least one noise characteristic and the model filters;   d) using the sufficient statistic for the desired data element to generate a subsurface image.   
   
   
       2 . The method of  claim 1  wherein at least one noise characteristic determined for the measured data elements comprises non-zero correlations between the noises in the measured data elements. 
   
   
       3 . (canceled) 
   
   
       4 . The method of  claim 2  wherein at least one data element is chosen from the group consisting of a seismic data trace, a portion of a seismic data trace, a collection of portions of seismic data traces deriving from nearby receiver locations, a collection of portions of seismic data traces having at least one subsurface reflection point near a common subsurface location, a collection of portions of seismic data traces deriving from nearby source locations and any combination thereof. 
   
   
       5 - 6 . (canceled) 
   
   
       7 . The method of  claim 1  wherein the sufficient statistic is the minimum variance unbiased estimate of the desired data element. 
   
   
       8 - 9 . (canceled) 
   
   
       10 . A method for combining at least two seismic data sets of a subsurface comprising:
 a) obtaining at least two measured data elements that contain information about a desired element,   b) determining at least one local parameter related to at least one property of the measured data elements,   c) calculating at least one model filter using at least one local parameter,   d) determining a noise covariance matrix of the measured data elements,   e) computing a sufficient statistic data element for the desired data element from the measured data elements based on at least one model filter and at least one noise covariance matrix,   f) using the desired data element to generate a subsurface image.   
   
   
       11 . The method of  claim 10  wherein the noise covariance matrix determined for the measured data elements comprises non-zero correlations between the data elements. 
   
   
       12 . The method of  claim 10  wherein the at least one model filter is a linear time-invariant and space-invariant filter specified in frequency/wavenumber domain. 
   
   
       13 . The element of  claim 11  wherein at least one data element is chosen from the group consisting of a seismic data trace, a portion of a seismic data trace, a collection of portions of seismic data traces deriving from nearby receiver locations, a collection of portions of seismic data traces having at least one subsurface reflection point near a common subsurface location, a collection of portions of seismic data traces deriving from nearby source locations and any combination thereof. 
   
   
       14 . The method of  claim 11  wherein at least one model filter is a linear time-invariant filter specified in frequency domain. 
   
   
       15 . (canceled) 
   
   
       16 . The method of  claim 10  wherein the sufficient statistic is the minimum variance unbiased estimate of the desired data element. 
   
   
       17 - 19 . (canceled) 
   
   
       20 . The method of  claim 1 , further comprising processing the sufficient statistic for the desired data element to form an estimate of the desired data element. 
   
   
       21 . The method of  claim 20 , wherein the forming step and the processing step are performed together in a single equivalent mathematical operation. 
   
   
       22 - 23 . (canceled) 
   
   
       24 . The method of  claim 10 , further comprising computing an estimate of the desired data element using the sufficient statistic data element. 
   
   
       25 . The method of  claim 24 , wherein step (e) and the step of computing an estimate of the desired data element using the sufficient statistic data element are performed together in a single equivalent mathematical operation. 
   
   
       26 . The method of  claim 24 , wherein the estimate of the desired data element is computed by using the sufficient statistic in calculating a minimum mean squared error estimate of the desired data element. 
   
   
       27 . The method of  claim 24 , wherein the estimate of the desired data element is computed by filtering the sufficient statistic in a wavelet basis to form an estimate of the desired data element. 
   
   
       28 . The method of  claim 1 , wherein the at least one noise characteristic is a noise covariance matrix of the measured data elements, and the model filters are determined using at least one local parameter characteristic of the measured data elements' measurement location. 
   
   
       29 . The method of  claim 28  wherein the noise covariance matrix of the measured data elements comprises non-zero correlations between the data elements. 
   
   
       30 . A method for combining at least two seismic data sets to generate a subsurface image, comprising:
 (a) selecting at least one measured data element from each of at least two of said seismic data sets;   (b) determining a measurement model comprising a desired data element and, for each selected measured data element, a filter that filters the desired data element to produce as output the selected measured data element with noise removed and a noise signal which, when added to the filter output produces the measured data element;   (c) determining an estimator (paragraph 37 &  FIG. 2 ) that receives as its inputs said measured data elements and produces as its output an estimate of said desired data element, wherein said estimate is a sufficient statistic for said desired data element and where said estimate is based at least on the filters in said measurement model and on at least one characteristic of said noise signals; and   (d) using said estimate for the desired data element to generate a subsurface image.   
   
   
       31 . The method of  claim 1 , wherein said seismic data sets differ in regard to age. 
   
   
       32 . The method of  claim 1 , wherein said seismic data sets differ in regard to acquisition technology. 
   
   
       33 . The method of  claim 1 , wherein said seismic data sets differ in regard to sensor type employed for acquisition. 
   
   
       34 . The method of  claim 1 , wherein said seismic data sets contain different source and receiver pairs. 
   
   
       35 . The method of  claim 1 , wherein forming a sufficient statistic assumes a Gaussian probability distribution for noise. 
   
   
       36 . The method of  claim 30 , wherein determination of whether an estimate forms a sufficient statistic for a desired data element assumes a Gaussian probability distribution for measurement model noise.