{"id":107764,"date":"2024-12-05T20:49:26","date_gmt":"2024-12-05T20:49:26","guid":{"rendered":"https:\/\/ahay.org\/blog\/?p=107764"},"modified":"2024-12-05T21:00:18","modified_gmt":"2024-12-05T21:00:18","slug":"least-squares-non-stationary-triangle-smoothing","status":"publish","type":"post","link":"https:\/\/ahay.org\/blog\/2024\/12\/05\/least-squares-non-stationary-triangle-smoothing\/","title":{"rendered":"Least-squares non-stationary triangle smoothing"},"content":{"rendered":"

An old paper is added to the collection of reproducible documents<\/a>: Least-squares non-stationary triangle smoothing<\/a><\/p>\n

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We propose a fast and accurate method to estimate the radius of non-stationary triangle smoothing for matching two seismic datasets. The smoothing radius is estimated by non-linear least-squares inversion using an iterative Gauss-Newton approach. We derive and implement the derivative of the smoothing operator to compute the gradient for inversion. The proposed method is useful for implementing non-stationary triangle smoothing as a low-cost edge-preserving filter. The efficiency of the proposed method is also confirmed in several field data examples of seismic data matching applications in non-stationary local signal and noise orthogonalization, non-stationary local slope estimation, and matching low-resolution and high resolution seismic images from the same exploration area.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"

An old paper is added to the collection of reproducible documents: Least-squares non-stationary triangle smoothing We propose a fast and accurate method to estimate the radius of non-stationary triangle smoothing for matching two seismic datasets. The smoothing radius is estimated by non-linear least-squares inversion using an iterative Gauss-Newton approach. We derive and implement the derivative […]<\/p>\n","protected":false},"author":17,"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":"","activitypub_max_image_attachments":4,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"federate","footnotes":""},"categories":[7],"tags":[],"class_list":["post-107764","post","type-post","status-publish","format-standard","hentry","category-examples"],"_links":{"self":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/107764","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\/17"}],"replies":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/comments?post=107764"}],"version-history":[{"count":2,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/107764\/revisions"}],"predecessor-version":[{"id":107784,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/107764\/revisions\/107784"}],"wp:attachment":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/media?parent=107764"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/categories?post=107764"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/tags?post=107764"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}