{"id":987739,"date":"2026-04-29T10:20:10","date_gmt":"2026-04-29T10:20:10","guid":{"rendered":"https:\/\/david.midstar.com.sa\/?page_id=987739"},"modified":"2026-06-04T13:51:43","modified_gmt":"2026-06-04T13:51:43","slug":"recording-length-and-sample-rate","status":"publish","type":"page","link":"https:\/\/david.midstar.com.sa\/?page_id=987739","title":{"rendered":"Recording length and sample rate"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"987739\" class=\"elementor elementor-987739\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b498114 e-flex e-con-boxed e-con e-parent\" data-id=\"b498114\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-71f54c3 elementor-widget elementor-widget-html\" data-id=\"71f54c3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"seismic-temporal-sampling-suite\" style=\"font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif; color: #334155; background: #ffffff; padding: 45px; border-radius: 12px; border: 1px solid #e2e8f0; max-width: 1100px; margin: 25px auto; box-shadow: 0 10px 25px -5px rgba(0,0,0,0.05); line-height: 1.8;\">\r\n\r\n    <div style=\"border-bottom: 2px solid #f1f5f9; padding-bottom: 26px; margin-bottom: 35px;\">\r\n        <span style=\"font-size: 11px; font-weight: 700; color: #0d9488; text-transform: uppercase; letter-spacing: 0.12em; display: block; margin-bottom: 8px;\">Temporal Signal Processing Matrix<\/span>\r\n        <h1 style=\"font-size: 28px; font-weight: 800; color: #0f172a; margin: 0; letter-spacing: -0.025em;\">Mechanics of Recording Length & Sampling Rate<\/h1>\r\n        <p style=\"font-size: 14px; color: #64748b; margin: 10px 0 0 0; max-width: 950px;\">\r\n            An engineering deep-dive on discrete temporal digitization thresholds, wave aliasing hazards, and total reflection window calculations in 2D and 3D exploration.\r\n        <\/p>\r\n    <\/div>\r\n\r\n    <div style=\"display: flex; flex-direction: column; gap: 40px;\">\r\n\r\n        <div>\r\n            <h2 style=\"font-size: 20px; font-weight: 700; color: #0f172a; margin: 0 0 14px 0; border-left: 4px solid #0d9488; padding-left: 12px;\">1. Temporal Digitization & The Sampling Rate<\/h2>\r\n            <p style=\"font-size: 14px; color: #475569; margin: 0 0 16px 0; text-align: justify;\">\r\n                Seismic instruments do not record a continuous analog line; they convert returning raw acoustic voltage waves into digital data packages by reading amplitude levels at precise time increments called the **Sampling Rate ($\\Delta t$)**. Standard exploration settings utilize intervals of 1, 2, or 4 milliseconds (ms).\r\n            <\/p>\r\n            <p style=\"font-size: 14px; color: #475569; margin: 0 0 20px 0; text-align: justify;\">\r\n                This choice sets the upper frequency limit for the entire data volume. If the sampling interval is too wide, complex fine-scale high-frequency structures cannot be mapped accurately.\r\n            <\/p>\r\n\r\n            <div style=\"margin: 25px auto; max-width: 750px; background: #0f172a; border-radius: 8px; padding: 25px; text-align: center; border: 1px solid #1e293b;\">\r\n                <div style=\"position: relative; height: 120px; margin-bottom: 15px; border-bottom: 1px solid #334155;\">\r\n                    <svg style=\"width: 100%; height: 100%;\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\r\n                        <path d=\"M 10 60 Q 60 -10, 110 60 T 210 60 T 310 60 T 410 60 T 510 60 T 610 60\" fill=\"none\" stroke=\"rgba(255,255,255,0.2)\" stroke-width=\"2\" \/>\r\n                        <circle cx=\"10\" cy=\"60\" r=\"4\" fill=\"#0d9488\" \/><line x1=\"10\" y1=\"60\" x2=\"10\" y2=\"120\" stroke=\"#0d9488\" stroke-dasharray=\"2\" \/>\r\n                        <circle cx=\"60\" cy=\"25\" r=\"4\" fill=\"#0d9488\" \/><line x1=\"60\" y1=\"25\" x2=\"60\" y2=\"120\" stroke=\"#0d9488\" stroke-dasharray=\"2\" \/>\r\n                        <circle cx=\"110\" cy=\"60\" r=\"4\" fill=\"#0d9488\" \/><line x1=\"110\" y1=\"60\" x2=\"110\" y2=\"120\" stroke=\"#0d9488\" stroke-dasharray=\"2\" \/>\r\n                        <circle cx=\"160\" cy=\"95\" r=\"4\" fill=\"#0d9488\" \/><line x1=\"160\" y1=\"95\" x2=\"160\" y2=\"120\" stroke=\"#0d9488\" stroke-dasharray=\"2\" \/>\r\n                        <circle cx=\"210\" cy=\"60\" r=\"4\" fill=\"#0d9488\" \/><line x1=\"210\" y1=\"60\" x2=\"210\" y2=\"120\" stroke=\"#0d9488\" stroke-dasharray=\"2\" \/>\r\n                        <circle cx=\"260\" cy=\"25\" r=\"4\" fill=\"#0d9488\" \/><line x1=\"260\" y1=\"25\" x2=\"260\" y2=\"120\" stroke=\"#0d9488\" stroke-dasharray=\"2\" \/>\r\n                        <circle cx=\"310\" cy=\"60\" r=\"4\" fill=\"#0d9488\" \/><line x1=\"310\" y1=\"60\" x2=\"310\" y2=\"120\" stroke=\"#0d9488\" stroke-dasharray=\"2\" \/>\r\n                    <\/svg>\r\n                    <div style=\"position: absolute; left: 10px; width: 50px; bottom: 5px; height: 10px; border-left: 1px solid #0d9488; border-right: 1px solid #0d9488; border-bottom: 1px solid #0d9488;\"><\/div>\r\n                    <div style=\"position: absolute; left: 22px; bottom: -8px; font-size: 10px; color: #0d9488; font-family: monospace;\">\u0394t<\/div>\r\n                <\/div>\r\n                <div style=\"font-size: 12px; color: #94a3b8; font-weight: 500;\">Figure 1: Analog Continuous Waveform vs. Discrete Digital Sample Intervals ($\\Delta t$)<\/div>\r\n            <\/div>\r\n        <\/div>\r\n\r\n        <div>\r\n            <h2 style=\"font-size: 20px; font-weight: 700; color: #0f172a; margin: 0 0 14px 0; border-left: 4px solid #b45309; padding-left: 12px;\">2. The Nyquist Shannon Criteria & Temporal Aliasing<\/h2>\r\n            <p style=\"font-size: 14px; color: #475569; margin: 0 0 16px 0; text-align: justify;\">\r\n                The maximum frequency a digital layout can reconstruct accurately is called the **Nyquist Frequency ($f_N$)**. The math underlying signal preservation defines the limit as exactly one-half cycles per sample unit:\r\n            <\/p>\r\n            \r\n            <div style=\"background: #f8fafc; border: 1px solid #e2e8f0; padding: 14px; border-radius: 6px; font-family: monospace; font-size: 16px; font-weight: 700; color: #0f172a; text-align: center; margin-bottom: 16px;\">\r\n                f<sub>Nyquist<\/sub> = 1 \/ (2 \u2022 \u0394t)\r\n            <\/div>\r\n\r\n            <p style=\"font-size: 14px; color: #475569; margin: 0 0 20px 0; text-align: justify;\">\r\n                If returning subterranean signal vibrations possess frequencies higher than $f_N$, the wave collapses into **Temporal Aliasing**. The high-frequency wave peaks bypass tracking readouts, appearing in final data storage files as false, distorted low-frequency masks.\r\n            <\/p>\r\n\r\n            <div style=\"margin: 25px auto; max-width: 750px; background: #0f172a; border-radius: 8px; padding: 25px; text-align: center; border: 1px solid #1e293b;\">\r\n                <div style=\"position: relative; height: 100px; margin-bottom: 10px;\">\r\n                    <svg style=\"width: 100%; height: 100%;\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\r\n                        <path d=\"M 10 50 Q 30 0, 50 50 T 90 50 T 130 50 T 170 50 T 210 50 T 250 50 T 290 50 T 330 50 T 370 50 T 410 50 T 450 50 T 490 50\" fill=\"none\" stroke=\"#ef4444\" stroke-width=\"1\" stroke-dasharray=\"2\" \/>\r\n                        <path d=\"M 10 50 Q 90 0, 170 50 T 330 50 T 490 50\" fill=\"none\" stroke=\"#38bdf8\" stroke-width=\"2\" \/>\r\n                        <circle cx=\"10\" cy=\"50\" r=\"4\" fill=\"#38bdf8\" \/>\r\n                        <circle cx=\"90\" cy=\"12\" r=\"4\" fill=\"#38bdf8\" \/>\r\n                        <circle cx=\"170\" cy=\"50\" r=\"4\" fill=\"#38bdf8\" \/>\r\n                        <circle cx=\"250\" cy=\"88\" r=\"4\" fill=\"#38bdf8\" \/>\r\n                        <circle cx=\"330\" cy=\"50\" r=\"4\" fill=\"#38bdf8\" \/>\r\n                    <\/svg>\r\n                <\/div>\r\n                <div style=\"font-size: 11px; color: #94a3b8; margin-bottom: 5px; font-family: monospace;\">\r\n                    <span style=\"color: #ef4444; margin-right: 15px;\">\u25cf High Frequency Wave (Aliased Out)<\/span> \r\n                    <span style=\"color: #38bdf8;\">\u25cf Reconstructed False Output Wave<\/span>\r\n                <\/div>\r\n                <div style=\"font-size: 12px; color: #94a3b8; font-weight: 500;\">Figure 2: Under-sampling high frequencies results in physical phase identity loss<\/div>\r\n            <\/div>\r\n        <\/div>\r\n\r\n        <div>\r\n            <h2 style=\"font-size: 20px; font-weight: 700; color: #0f172a; margin: 0 0 14px 0; border-left: 4px solid #db2777; padding-left: 12px;\">3. Calculating Total Target Recording Length<\/h2>\r\n            <p style=\"font-size: 14px; color: #475569; margin: 0 0 16px 0; text-align: justify;\">\r\n                **Recording Length ($T$)** represents the duration (in seconds) that the acquisition arrays record incoming ground data after energy discharge. It must be long enough to catch the deepest primary energy reflection plus any late-arriving structures.\r\n            <\/p>\r\n            <div style=\"background: #fffbeb; border: 1px solid #fef3c7; padding: 16px; border-radius: 8px; margin-bottom: 16px; font-family: monospace; font-size: 14px; color: #78350f; text-align: center;\">\r\n                Total Listening Window (T) \u2265 TWT<sub>deepest<\/sub> + T<sub>moveout<\/sub> + T<sub>processing_window<\/sub>\r\n            <\/div>\r\n            <p style=\"font-size: 14px; color: #475569; margin: 0; text-align: justify;\">\r\n                If your recording window cuts off too early, the deepest target reflectors are truncated from your final cross-section. On the other hand, recording for too long increases data storage overhead and inflates processing costs across millions of channels without adding real structural resolution.\r\n            <\/p>\r\n        <\/div>\r\n\r\n    <\/div>\r\n\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Temporal Signal Processing Matrix Mechanics of Recording Length &#038; Sampling Rate An engineering deep-dive on discrete temporal digitization thresholds, wave aliasing hazards, and total reflection window calculations in 2D and 3D exploration. 1. Temporal Digitization &#038; The Sampling Rate Seismic instruments do not record a continuous analog line; they convert returning raw acoustic voltage waves&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"footnotes":""},"class_list":["post-987739","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/david.midstar.com.sa\/index.php?rest_route=\/wp\/v2\/pages\/987739","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/david.midstar.com.sa\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/david.midstar.com.sa\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/david.midstar.com.sa\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/david.midstar.com.sa\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=987739"}],"version-history":[{"count":4,"href":"https:\/\/david.midstar.com.sa\/index.php?rest_route=\/wp\/v2\/pages\/987739\/revisions"}],"predecessor-version":[{"id":987860,"href":"https:\/\/david.midstar.com.sa\/index.php?rest_route=\/wp\/v2\/pages\/987739\/revisions\/987860"}],"wp:attachment":[{"href":"https:\/\/david.midstar.com.sa\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=987739"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}