Abstract：
Accurately estimated interval attenuation (1/Q) values have several applications, such as in quantitative interpretation and seismic resolution enhancement. Although Q values can be estimated by measuring the spectral ratio between seismic reflections from a target and a reference reflector, the results are influenced by factors such as overburden inhomogeneities. Here, we quantitatively analyze the overburden influence on interval Q estimations using the spectral ratio method, time–space domain prestack Q inversion (PSQI), and τ-p domain PSQI. We compare these three methods using a synthetic dataset and a field dataset acquired onshore the Arabian Peninsula. Synthetic seismic gathers are generated from a three-layer model with a low-Q inclusion in the first layer to mimic overburden inhomogeneity. The fi eld data are preconditioned image gathers from a producing oil fi eld. The synthetic data test shows that the small low-Q body produces a considerable error in estimated Q values. The smallest error (i.e., 13.3%) is in the τ-p domain PSQI result. Theoretically, τ-p domain PSQI could obtain more accurate Q values when there are overburden influences because of the simultaneous inversion scheme and the application in the τ-p domain. The fi eld data application also illustrates that the τ-p domain PSQI produces reasonable interval Q values. Our measured Q values are also comparable with the Q values estimated from hydrocarbon saturated carbonate reservoirs.
作者简介: Abdullah Alshangiti received his BSc in Geophysics from King Abdulaziz University in 2006. In 2010, he was awarded an MSc degree with merit in Petroleum Geology and Geophysics from the University of Leeds. Abdullah worked as a seismic data processing geophysicist for the Geophysical Imaging Department at Saudi Aramco for 7 years before starting his Ph.D. program in 2017. He is currently a Ph.D. student in Geophysics at the University of Houston. His main research interests are seismic processing, inversion and attenuation estimation for quantitative interpretation, inverse Q-fi ltering.. Main and Corresponding Author: Mr. Abdullah Alshangiti, University of Houston, Department of Earth and Atmospheric Sciences, Houston, Texas, The United States (Email: abdullah.shangiti@gmail.com).
Co-author: Dr. Hua-Wei Zhou, University of Houston, Department of Earth and Atmospheric Sciences, Houston, Texas, The United States (Email: hzhou@uh.edu).
2020, Vol. 17 
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