{"id":102583,"date":"2020-07-18T20:49:29","date_gmt":"2020-07-18T20:49:29","guid":{"rendered":"http:\/\/ahay.org\/blog\/?p=102583"},"modified":"2020-07-18T20:51:29","modified_gmt":"2020-07-18T20:51:29","slug":"application-of-principal-component-analysis-in-weighted-stacking-of-seismic-data","status":"publish","type":"post","link":"https:\/\/ahay.org\/blog\/2020\/07\/18\/application-of-principal-component-analysis-in-weighted-stacking-of-seismic-data\/","title":{"rendered":"Application of principal component analysis in weighted stacking of seismic data"},"content":{"rendered":"<p>A new paper is added to the <a href=\"\/wiki\/Reproducible_Documents\">collection of reproducible documents<\/a>: <a href=\"\/RSF\/book\/tccs\/pcastack\/paper_html\/\">Application of principal component analysis in weighted stacking of seismic data<\/a><\/p>\n<p><img decoding=\"async\" src=\"\/RSF\/book\/tccs\/pcastack\/Fig\/zoom1.png\" alt=\"\" title=\"\"><br \/>\n<img decoding=\"async\" src=\"\/RSF\/book\/tccs\/pcastack\/Fig\/zoom3.png\" alt=\"\" title=\"\"><\/p>\n<blockquote><p>Optimal stacking of multiple datasets plays a significant role in many scientific domains. The quality of stacking will affect the signal-to-noise ratio (SNR) and amplitude fidelity of the stacked image. In seismic data processing, the similarity-weighted stacking makes use of the local similarity between each trace and a reference trace as the weight to stack the flattened prestack seismic data after normal moveout (NMO) correction. The traditional reference trace is an approximated zero-offset trace that is calculated from a direct arithmetic mean of the data matrix along the spatial direction. However, in the case that the data matrix contains abnormal mis-aligned trace, erratic and non-gaussian random noise, the accuracy of the approximated zero-offset trace would be greatly affected, thereby further influence the quality of stacking. We propose a novel weighted stacking method that is based on principal component analysis (PCA). The principal components of the data matrix, namely the useful signals, are extracted based on a low-rank decomposition method by solving an optimization problem with a low-rank constraint. The optimization problem is solved via a common singular value decomposition algorithm. The low-rank decomposition of the data matrix will alleviate the influence of abnormal trace, erratic and non-gaussian random noise, thus will be more robust than the traditional alternatives. We use both synthetic and field data examples to show the successful performance of the proposed approach.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>A new paper is added to the collection of reproducible documents: Application of principal component analysis in weighted stacking of seismic data Optimal stacking of multiple datasets plays a significant role in many scientific domains. The quality of stacking will affect the signal-to-noise ratio (SNR) and amplitude fidelity of the stacked image. In seismic data [&hellip;]<\/p>\n","protected":false},"author":15,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","activitypub_content_warning":"","activitypub_content_visibility":"local","activitypub_max_image_attachments":4,"activitypub_interaction_policy_quote":"","footnotes":""},"categories":[5],"tags":[],"class_list":["post-102583","post","type-post","status-publish","format-standard","hentry","category-documentation"],"_links":{"self":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/102583","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/comments?post=102583"}],"version-history":[{"count":3,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/102583\/revisions"}],"predecessor-version":[{"id":102587,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/102583\/revisions\/102587"}],"wp:attachment":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/media?parent=102583"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/categories?post=102583"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/tags?post=102583"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}