Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval
It is important to be able to detect and characterize naturally occurring fractures in reservoirs using surface seismic reflection data. 3D finite difference elastic modeling is used to create simulated surface seismic data over a three layer model and a five layer model. The elastic properties in...
| Main Authors: | , , , |
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| Format: | Technical Report |
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Massachusetts Institute of Technology. Earth Resources Laboratory
2011
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| Online Access: | http://hdl.handle.net/1721.1/67868 |
| _version_ | 1811071270190579712 |
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| author | Willis, Mark E. Burns, Daniel R. Rao, Rama V. N. Minsley, Burke J. |
| author2 | Massachusetts Institute of Technology. Earth Resources Laboratory |
| author_facet | Massachusetts Institute of Technology. Earth Resources Laboratory Willis, Mark E. Burns, Daniel R. Rao, Rama V. N. Minsley, Burke J. |
| author_sort | Willis, Mark E. |
| collection | MIT |
| description | It is important to be able to detect and characterize naturally occurring fractures in reservoirs using surface seismic
reflection data. 3D finite difference elastic modeling is used to create simulated surface seismic data over a three layer model and a
five layer model. The elastic properties in the reservoir layer of each model are varied to simulate different amounts of vertical parallel
fracturing. The presence of the fractures induces ringing wave trains primarily at times later than the bottom reservoir reflection.
These ringy or scattered wave trains appear coherent on the seismograms recorded parallel to the fracture direction. While there are
many scattered events on the seismograms recorded perpendicular to the direction of the fractures, these events appear to generally
stack out during conventional processing.
A method of characterizing and detecting scattering in intervals is developed by deconvolution to give an interval transfer
function. The method is simple for the case of two isolated reflections, one from the top of the reservoir and the other from the bottom
of the reservoir. The transfer function is computed using the top reflection as the input and the bottom reflection as the output. The
transfer function then characterizes the effect of the scattering layer. A simple pulse shape indicates no scattering. A long ringy
transfer function captures the scattering within the reservoir interval. When analyzing field data, it is rarely possible to isolate
reflections. Therefore, an adaptation of the method is developed using autocorrelations of the wave trains above (as input) and below
(as output) the interval of interest for the deconvolution process. The presence of fractures should be detectable from observed ringy
transfer functions computed for each time interval. The fracture direction should be identifiable from azimuthal variations – there
should be more ringiness in the direction parallel to fracturing. The method applied to ocean bottom cable field data at 4 locations
show strong temporal and azimuthal variations of the transfer function which may be correlated to the known geology. |
| first_indexed | 2024-09-23T08:48:32Z |
| format | Technical Report |
| id | mit-1721.1/67868 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T08:48:32Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology. Earth Resources Laboratory |
| record_format | dspace |
| spelling | mit-1721.1/678682019-04-10T19:10:06Z Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval Willis, Mark E. Burns, Daniel R. Rao, Rama V. N. Minsley, Burke J. Massachusetts Institute of Technology. Earth Resources Laboratory Willis, Mark E. Burns, Daniel R. Rao, Rama V. N. Minsley, Burke J. It is important to be able to detect and characterize naturally occurring fractures in reservoirs using surface seismic reflection data. 3D finite difference elastic modeling is used to create simulated surface seismic data over a three layer model and a five layer model. The elastic properties in the reservoir layer of each model are varied to simulate different amounts of vertical parallel fracturing. The presence of the fractures induces ringing wave trains primarily at times later than the bottom reservoir reflection. These ringy or scattered wave trains appear coherent on the seismograms recorded parallel to the fracture direction. While there are many scattered events on the seismograms recorded perpendicular to the direction of the fractures, these events appear to generally stack out during conventional processing. A method of characterizing and detecting scattering in intervals is developed by deconvolution to give an interval transfer function. The method is simple for the case of two isolated reflections, one from the top of the reservoir and the other from the bottom of the reservoir. The transfer function is computed using the top reflection as the input and the bottom reflection as the output. The transfer function then characterizes the effect of the scattering layer. A simple pulse shape indicates no scattering. A long ringy transfer function captures the scattering within the reservoir interval. When analyzing field data, it is rarely possible to isolate reflections. Therefore, an adaptation of the method is developed using autocorrelations of the wave trains above (as input) and below (as output) the interval of interest for the deconvolution process. The presence of fractures should be detectable from observed ringy transfer functions computed for each time interval. The fracture direction should be identifiable from azimuthal variations – there should be more ringiness in the direction parallel to fracturing. The method applied to ocean bottom cable field data at 4 locations show strong temporal and azimuthal variations of the transfer function which may be correlated to the known geology. Massachusetts Institute of Technology. Earth Resources Laboratory United States. Dept. of Energy (Grant DE-FC26-02NT15346) Eni S.p.A. (Firm) 2011-12-21T23:22:57Z 2011-12-21T23:22:57Z 2003 Technical Report http://hdl.handle.net/1721.1/67868 Earth Resources Laboratory Industry Consortia Annual Report;2003-08 application/pdf Massachusetts Institute of Technology. Earth Resources Laboratory |
| spellingShingle | Willis, Mark E. Burns, Daniel R. Rao, Rama V. N. Minsley, Burke J. Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval |
| title | Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval |
| title_full | Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval |
| title_fullStr | Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval |
| title_full_unstemmed | Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval |
| title_short | Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval |
| title_sort | characterization of scattered waves from fractures by estimating the transfer function between reflected events above and below each interval |
| url | http://hdl.handle.net/1721.1/67868 |
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