none 10.1190/tle36080688.1 Society of Exploration Geophysicists Society of Exploration Geophysicists 186 92001196 5980 2025120815020100700 10.1190 2025-12-08T20:02:12Z 2017-07-28T09:06:21Z 3 The Leading Edge 1070-485X 08 2017 08 01 2017 36 8 Felix Oghenekohwo 1 Seismic Laboratory for Imaging and Modeling (SLIM), The University of British Columbia. Felix J. Herrmann 1 Seismic Laboratory for Imaging and Modeling (SLIM), The University of British Columbia. http://orcid.org/0000-0003-1180-2167 Abstract Recently, we demonstrated that combining joint recovery with low-cost nonreplicated randomized sampling tailored to time-lapse seismic can give us access to high-fidelity, highly repeatable, dense prestack vintages, and high-grade time lapse. To arrive at this result, we assumed well-calibrated surveys — i.e., we presumed accurate postplot source/receiver positions. Unfortunately, in practice, seismic surveys are prone to calibration errors, which are unknown deviations between actual and postplot acquisition geometry. By means of synthetic experiments, we analyze the possible impact of these errors on vintages and on time-lapse data obtained with our joint-recovery model from compressively sampled surveys. Supported by these experiments, we demonstrate that highly repeatable time-lapse vintages are attainable despite the presence of unknown calibration errors in the positions of the shots. We assess the repeatability quantitatively for two scenarios by studying the impact of calibration errors on conventional dense but irregularly sampled surveys and on low-cost compressed surveys. To separate time-lapse effects from calibration issues, we consider the idealized case in which the subsurface remains unchanged and the practical situation in which time-lapse changes are restricted to a subset of the data. In both cases, the quality of the recovered vintages and time lapse decreases gracefully for low-cost compressed surveys with increasing calibration errors. Conversely, the quality of vintages from expensive densely periodically sampled surveys decreases more rapidly as unknown and difficult-to-control calibration errors increase. 08 2017 08 01 2017 688 694 1 10.1190/crossmark-policy library.seg.org true 2017-07-28 10.1190/tle36080688.1 https://pubs.geoscienceworld.org/tle/article/36/8/688/353510/Highly-repeatable-time-lapse-seismic-with https://pubs.geoscienceworld.org/seg/tle/article-pdf/36/8/688/7437841/tle36080688.1.pdf https://pubs.geoscienceworld.org/seg/tle/article-pdf/36/8/688/7437841/tle36080688.1.pdf https://pubs.geoscienceworld.org/tle/article/36/8/688/353510/highly-repeatable-time-lapse-seismic-with Distributed compressive sensing 2009 First Break 29 11 49 2011 Improved marine 4D repeatability using an automated vessel, source and receiver positioning system IEEE Transactions on Information Theory 52 2 489 2006 10.1109/TIT.2005.862083 Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information IEEE Transactions on Information Theory 52 4 1289 2006 10.1109/TIT.2006.871582 Compressed sensing The Leading Edge 33 2 150 2014 10.1190/tle33020150.1 Multisensor streamer recording and its implications for time-lapse seismic and repeatability Geophysics 68 4 1303 2003 10.1190/1.1598123 A proven method for acquiring highly repeatable towed streamer seismic data 75th Annual International Meeting, SEG, Expanded Abstracts 2410 2005 Prestack repeatability of time-lapse seismic data Geophysics 73 3 V19 2008 10.1190/1.2841038 Simply denoise: Wavefield reconstruction via jittered undersampling Geophysics 75 6 WB173 2010 10.1190/1.3506147 Randomized sampling and sparsity: Getting more information from fewer samples The Leading Edge 33 2 172 2014 10.1190/tle33020172.1 An efficient 4D processing flow for variable-depth streamer data The Leading Edge 26 7 828 2007 10.1190/1.2756860 Time-lapse seismic repeatability — How much is enough? The Leading Edge 21 7 640 2002 10.1190/1.1497316 Seismic repeatability, normalized rms, and predictability The Leading Edge 36 2017 Highly repeatable 3D compressive full-azimuth towed-streamer time-lapse acquisition — A numerical feasibility study at scale Geophysical Prospecting 60 4 648 2012 10.1111/j.1365-2478.2012.01075.x Randomized marine acquisition with compressive sampling matrices The Leading Edge 33 4 386 2014 10.1190/tle33040386.1 Increasing the efficiency of seismic data acquisition via compressive sensing Geophysics 82 3 P1 2017 10.1190/geo2016-0076.1 Low-cost time-lapse seismic with distributed compressive sensing — Part 1: Exploiting common information among the vintages Geophysics 66 4 1015 2001 10.1190/1.1487049 Cross-equalization data processing for time-lapse seismic reservoir monitoring: A case study from the Gulf of Mexico Repeatability processing tests: Offshore Technology Conference, paper OTC-8311-MS 1997 Time-lapse seismic monitoring 71st Conference and Exhibition, EAGE, Extended Abstracts 2009 Seismic repeatability — Is there a limit? 83rd Annual International Meeting, SEG, Expanded Abstracts 1 2013 Time-jittered ocean bottom seismic acquisition Geophysics 82 3 P15 2017 10.1190/geo2016-0252.1 Low-cost time-lapse seismic with distributed compressive sensing — Part 2: Impact on repeatability