Thomas A. Dickens - Houston TX, US Charlie Jing - Houston TX, US Dennis E. Willen - Houston TX, US
Assignee:
ExxonMobil Upstream Research Co. - Houston TX
International Classification:
G01V 1/40
US Classification:
702 11
Abstract:
Method for identifying, determining and correcting source-related phase errors in data from a controlled source electromagnetic survey by using data from ordinary survey receivers, i. e. without benefit of source monitoring data. Abrupt anomalies indicating source malfunctions are identified () in the time domain by plotting time intervals between neighboring zero crossings or by zero-lag cross correlation between consecutive bins of receiver data, and the amount of the time error () can be determined by performing cross correlation between two bins on either side of an anomaly. In the frequency domain, transmitter anomalies can be identified by looking for discontinuities in plots of phase vs. offset, and the corrective phase shift can be determined by matching the phase on one side of the anomaly to that on the other side. A global time/phase shift () can be determined by using phase frequency-scaling behavior at near offsets.
Iterative Inversion Of Data From Simultaneous Geophysical Sources
Jerome R. Krebs - Houston TX, US John E. Anderson - Houston TX, US Ramesh Neelamani - Houston TX, US Charlie Jing - Houston TX, US David Hinkley - Spring TX, US Thomas A. Dickens - Houston TX, US Christine E. Krohn - Houston TX, US Peter Traynin - Cypress TX, US
Assignee:
ExxonMobil Upstream Research Company - Houston TX
International Classification:
G06G 7/48
US Classification:
703 10
Abstract:
Method for reducing the time needed to perform geophysical inversion by using simultaneous encoded sources in the simulation steps of the inversion process. The geophysical survey data are prepared by encoding () a group of source gathers (), using for each gather a different encoding signature selected from a set () of non-equivalent encoding signatures. Then, the encoded gathers are summed () by summing all traces corresponding to the same receiver from each gather, resulting in a simultaneous encoded gather. (Alternatively, the geophysical data are acquired from simultaneously encoded sources. ) The simulation steps needed for inversion are then calculated using a particular assumed velocity (or other physical property) model () and simultaneously activated encoded sources using the same encoding scheme used on the measured data. The result is an updated physical properties model () that may be further updated () by additional iterations.
Inversion Of Csem Data With Measurement System Signature Suppression
Xinyou Lu - Missouri City TX, US Charlie Jing - Houston TX, US Thomas A. Dickens - Houston TX, US Dennis E. Willen - Houston TX, US
Assignee:
ExxonMobil Upstream Research Company - Houston TX
International Classification:
G06G 7/48
US Classification:
703 10
Abstract:
A method for suppressing measurement system signature, or artifacts, that arise when controlled source electromagnetic survey data are inverted to obtain a resistivity image of a subsurface region. The method involves identifying regions () where the image has low or rapidly varying sensitivity to data acquired by a given receiver, typically regions close to and under the given receiver. Then, in the iterative inversion process where a resistivity model is updated to minimize an objective function, the model update is modified () to reduce the impact of such low sensitivity regions on the update.
Iterative Inversion Of Data From Simultaneous Geophysical Sources
Jerome R. Krebs - Houston TX, US John E. Anderson - Houston TX, US Ramesh Neelamani - Houston TX, US Charlie Jing - Houston TX, US David Hinkley - Spring TX, US Thomas A. Dickens - Houston TX, US Christine E. Krohn - Houston TX, US Peter Traynin - Cypress TX, US
Assignee:
ExxonMobil Upstream Research Company - Houston TX
International Classification:
G06G 7/48
US Classification:
703 10
Abstract:
Method for reducing the time needed to perform geophysical inversion by using simultaneous encoded sources in the simulation steps of the inversion process. The geophysical survey data are prepared by encoding () a group of source gathers (), using for each gather a different encoding signature selected from a set () of non-equivalent encoding signatures. Then, the encoded gathers are summed () by summing all traces corresponding to the same receiver from each gather, resulting in a simultaneous encoded gather. (Alternatively, the geophysical data are acquired from simultaneously encoded sources. ) The simulation steps needed for inversion are then calculated using a particular assumed velocity (or other physical property) model () and simultaneously activated encoded sources using the same encoding scheme used on the measured data. The result is an updated physical properties model () that may be further updated () by additional iterations.
Charlie Jing - Houston TX, US Jim J. Carazzone - Houston TX, US Eva-Maria Rumpfhuber - Houston TX, US Rebecca L. Saltzer - Houston TX, US Thomas A. Dickens - Houston TX, US Anoop A. Mullur - Houston TX, US
International Classification:
G01V 1/28
US Classification:
367 73
Abstract:
Method for using seismic data from earthquakes to address the low frequency lacuna problem in traditional hydrocarbon exploration methods. Seismometers with frequency response Select Receivers of Desired Frequency Ranges and Design Survey Seismometer Configuration down to about Hz are placed over a target subsurface region in an array with spacing suitable for hydrocarbon exploration (). Data are collected over a long (weeks or months) time period (). Segments of the data () are identified with known events from earthquake catalogs (). Those data segments are analyzed using techniques such as trayeltime delay measurements () or receiver function calculations () and then are combined with one or more other types of geophysical data acquired from the target region, using joint inversion (-) in some embodiments of the method, to infer physical features of the subsurface indicative of hydrocarbon potential or lack thereof ().
Constructing Resistivity Models From Stochastic Inversion
Thomas A. Dickens - Houston TX, US Dennis E. Willen - Houston TX, US
International Classification:
E21B 43/00 G06G 7/48 G06F 17/10
US Classification:
166369, 703 2, 703 6, 703 10
Abstract:
Embodiments described herein use stochastic inversion () in lower dimensions to form an initial model () that is to be used in higher-dimensional gradient-based inversion (). For example, an initial model may be formed from 1.5-D stochastic inversions, which is then processed () to form a 3-D model. Stochastic inversions reduce or avoid local minima and may provide an initial result that is near the global minimum.
Ramesh Neelamani - Houston TX, US Partha S. Routh - Katy TX, US Jerome R. Krebs - Houston TX, US Anatoly Baumstein - Houston TX, US Thomas A. Dickens - Houston TX, US
International Classification:
G01V 1/28
US Classification:
367 38
Abstract:
Provided is a method for processing seismic data. One exemplary embodiment includes the steps of obtaining a plurality of initial subsurface images; decomposing each of the initial subsurface images into components; identifying a set of components comprising one of (i) components having at least one substantially similar characteristic across the plurality of initial subsurface images, and (ii) components having substantially dissimilar characteristics across the plurality of initial subsurface images; and generating an enhanced subsurface image using the identified set of components. Each of the initial subsurface images is generated using a unique random set of encoding functions.
Ramesh Neelamani - Houston TX, US Partha S. Routh - Katy TX, US Jerome R. Krebs - Houston TX, US Anatoly Baumstein - Houston TX, US Thomas A. Dickens - Houston TX, US Warren S. Ross - Houston TX, US Gopalkrishna Palacharla - Houston TX, US
International Classification:
G01V 1/28
US Classification:
367 73
Abstract:
The invention includes a method for reducing noise in migration of seismic data, particularly advantageous for imaging by simultaneous encoded source reverse-time migration (SS-RTM). One example embodiment includes the steps of obtaining a plurality of initial subsurface images; decomposing each of the initial subsurface images into components; identifying a set of components comprising one of (i) components having at least one substantially similar characteristic across the plurality of initial subsurface images, and (ii) components having substantially dissimilar characteristics across the plurality of initial subsurface images; and generating an enhanced subsurface image using the identified set of components. For SS-RTM, each of the initial subsurface images is generated by migrating several sources simultaneously using a unique random set of encoding functions. Another embodiment of the invention uses SS-RTM for velocity model building.