TY - GEN

T1 - Velocity analysis and event estimation for passive seismic data using source focusing function

AU - Song, Chao

AU - Alkhalifah, Tariq Ali

AU - Wu, Zedong

N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We thank KAUST for sponsoring this research. We also thank our SWAG colleagues for their helpful suggestions, especially Hanchen Wang. We thank Ye Lin and Dr.Yuyang Tan from University of Science and Technology of China for their fruitful discussions and providing the field data.

PY - 2018/8/27

Y1 - 2018/8/27

N2 - Attaining information corresponding to the passive seismic source location often helps in understanding the reservoir fracturing process. Time reversal based migration methods are widely used to find the source location directly. Such source locating methods share a fundamental weakness: The the accuracy of source image depends highly on the accuracy of the velocity model. In order to solve this problem, we introduce a new objective function to optimize the velocity model and source image at a much higher quality. Since the source energy does not focus well when the velocity is inaccurate, we utilize a source penalty function, which is often used to measure the source focusing as an objective function. The source in the objective function is defined by the estimated source coordinates and source image. In order to get high-resolution source images, we use the geometric mean imaging condition. The simultaneous update of the velocity, source image and location allows us to fit the objective for all these attributes of the model and source. Applications on data generated using the 2D Marmousi and field data show that the proposed method can improve the velocity model and source image quality.

AB - Attaining information corresponding to the passive seismic source location often helps in understanding the reservoir fracturing process. Time reversal based migration methods are widely used to find the source location directly. Such source locating methods share a fundamental weakness: The the accuracy of source image depends highly on the accuracy of the velocity model. In order to solve this problem, we introduce a new objective function to optimize the velocity model and source image at a much higher quality. Since the source energy does not focus well when the velocity is inaccurate, we utilize a source penalty function, which is often used to measure the source focusing as an objective function. The source in the objective function is defined by the estimated source coordinates and source image. In order to get high-resolution source images, we use the geometric mean imaging condition. The simultaneous update of the velocity, source image and location allows us to fit the objective for all these attributes of the model and source. Applications on data generated using the 2D Marmousi and field data show that the proposed method can improve the velocity model and source image quality.

UR - http://hdl.handle.net/10754/631154

UR - https://library.seg.org/doi/10.1190/segam2018-2989719.1

UR - http://www.scopus.com/inward/record.url?scp=85059361094&partnerID=8YFLogxK

U2 - 10.1190/segam2018-2989719.1

DO - 10.1190/segam2018-2989719.1

M3 - Conference contribution

SP - 2927

EP - 2931

BT - SEG Technical Program Expanded Abstracts 2018

PB - Society of Exploration Geophysicists

ER -