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Objectives the Multiple Large Blind Thrust Faults Capable of Generating

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Objectives the Multiple Large Blind Thrust Faults Capable of Generating Objectives The multiple large blind thrust faults capable of generating large-magnitude earthquakes that underlie the Los Angeles metropolitan area represent one of the most critical seismic risks in southern California [Dolan et al., 1995; Shaw et al., 2002; Dolan et al., 2003; Field et al., 2005]. Despite this recognition, as well as significant advances in documenting the earthquake history, geometry, and slip rates on these structures, we still do not fully understand how coseismic deformation is manifest at the surface above these blind thrusts in large-magnitude events. The July 21, 1952 Mw 7.3 Kern County earthquake was generated by a multi- segment rupture of an ~50-km-long section of the White Wolf fault, a major south- dipping thrust fault beneath the southernmost San Joaquin Valley and western Tehachapi Mountains [Steinbrugge and Moran, 1954; Jenkins and Oakeshott, 1955; Bolt, 1978; Stein and Thatcher, 1981; Wallace and Junkyoung, 1989; Dreger and AOI Figure 1. Regional setting of study area, with quaternary faults (red), seismicity (purple), and coseismic deformation associated with the 1952 Kern County Earthquake denoted. Location of the main area of focus for this study (yellow) is highlighted. Savage, 1999]. While the eastern half of the 1952 rupture generated small- displacement surface rupture (~1m offset), the western half of the rupture, including the location of the hypocenter, occurred as a blind thrust event [Jenkins and Oakeshott, 1955] (Figure 1). As such, it presents a unique opportunity to relate the observed coseismic surface deformation pattern associated with a large blind thrust earthquake to the geometry and location of folding related to previous events in the subsurface, thus informing our ability to infer this relationship more confidently for other blind thrusts for which coseismic deformation has not yet occurred in the historic era, or for which the acquisition of such data is difficult due to circumstances of geologic conditions or land use. Following the highly successful two-stage approach employed in previous studies of blind thrust faults [e.g., Oskin et al., 2000; Shaw et al., 2002; Pratt et al., 2002; Dolan et al., 2003; Leon et al., 2009], we have undertaken the first stage of such an analysis of this structure aimed at documenting the location, geometry, and ages of folding events that have occurred on the White Wolf blind thrust fault. Methodology CharacteriZing the geometry of the White Wolf Fault and associated folding, and its relationship to coseismic deformation for the 1952 Kern County Earthquake required two steps for this initial phase of the project. First, it was necessary to compile all of the available surface and subsurface geological and geophysical data, in some cases digitiZe and georeference it from publications, and place it all within a single project so that it could be jointly analyZed (Figure 1). A location was then identified for acquisition of a seismic reflection profile optimiZed to image the folded sediments overlying the blind thrust fault (as constrained by the compiled data), and these data were acquired using nodal seismometers and a vibroseis source in January of 2019. The seismic reflection acquisition required balancing two competing objectives. Due to the lack of surface topographic expression, sparsely-spaced subsurface constraints from existing data, and limited spatial resolution of coseismic information, a long seismic reflection profile was necessary to provide the greatest likelihood of capturing the fold scarp. On the other hand, because we want to be able to observe the shallowest possible manifestation of the fold scarp in the subsurface in order to delineate a target for potential shallow boreholes to age date the most recent events, a close receiver spacing was required in order to provide the possibility of imaging these reflectors that are associated with the most recent surface folding events. Therefore, we balanced these two objectives with the instruments and source options permitted by the available budget, to create a source and acquisition geometry optimiZed to satisfying these dual objectives. After evaluating a range of alternatives, we decided that contracting a large vibroseis source and nodal seismic array (supplemented with additional compatible nodal seismometers owned by the seismology group at the University of AriZona) through NodalSeismic allowed us to maximiZe the quality and quantity of data acquired while satisfying our multiple imaging objectives and fitting within our budget constraints. We designed the survey as follows: a single 4.83 km long North-South oriented line (along Edison Road), with receivers spaced at 15 foot intervals. The nodal seismometers recorded data continuously at a 1 ms sample rate, and the instruments were buried to ensure optimal coupling and decrease noise. The vibroseis source performed two linear sweeps from 10 to 120 HertZ for 18 seconds; shots were spaced at 15-foot intervals. Surveying, laying out, and deploying seismometers required 1.5 days in the field (Figure 2), testing of the source and running the vibroseis source required 2.5 days, and undeploying and collecting the seismometers required an additional day in the field. Because of the use of nodal seismometers, all instruments were laid out for all of the active source shots; as a result, we were able to maximiZe the fold of the data (improving signal-to-noise ratio). Additionally, because the instruments were continuously recording data the duration of the experiment (4-5 days, depending on when the specific instrument was deployed and undeployed), we have a continuous seismic record for a dense seismic array over this time period. These continuous data will be processed to look for local microseismicity Figure 2. Students from the University of Arizona deploying nodal that could be associated with seismometers for the seismic reflection acquisition associated with this study. the White Wolf fault, further supplementing the interpretation to improve our understanding of the fault; additional analyses of more regional seismicity could also be undertaken in the future. These data will be processed in the Promax software package, an industry- standard software for seismic reflection processing, using standard algorithms and approaches for processing. The resulting seismic reflection image will then be interpreted and placed within the framework of the other existing surface and subsurface data. The geometry of the fold and fault will be modeled using existing structural geologic kinematic concepts for fault propagation folding [Allmendinger, 1998; Suppe and Medwedeff, 1990]; should no models for the geometric relationships prove to be a satisfactory fit to the observed geometry, PI Hughes will conduct mechanical modeling using the discrete element modeling method to gain insight into the mechanical controls on the variations, as has been undertaken in related studies [Benesh et al., 2014; Hughes and Shaw, 2015, and others]. Results Through the duration of the grant timeframe, PI Hughes and a first-year MS graduate student at the University of AriZona worked together to compile the existing surface and subsurface data constraining the geometry of the White Wolf fault and associated folding with the coseismic observations from the 1952 Kern County Earthquake. These data were used to plan and optimiZe the final survey location and acquisition parameters for the seismic reflection survey. Further work consisted of evaluating different options for contracting a seismic source, working with Kern County officials to acquire the necessary permits for this acquisition, and arrange for the logistical needs of the seismic acquisition. Finally, we recently completed the field component of this study; the data have been downloaded, and a preliminary look at the raw data indicates that the data are of high quality and are likely to yield a high quality image in both the shallow and deep portions of the structure. Because the data were acquired six weeks ago, we are still in the preliminary phase of pre-processing of the data. These data will be processed under the direction of PI Johnson by two graduate students at the University of AriZona in the coming months; one student will optimiZe processing for imaging the deep geometry of the structure, while another will optimiZe processing for imaging the shallowest reflectors in the near subsurface. The primary student who is involved in this project will make the processing and integrated interpretation the basis for his MS thesis dissertation; because he is funded under the NSF Bridge-to-Doctorate program, and is jointly advised by PIs Hughes and Johnson, he will have ample support to successfully complete this project. We anticipate sharing the results of the seismic processing at the SCEC annual meeting in fall 2019, and writing and submitting for publication the results of the integrated study in 2020. References Allmendinger, R., 1998. Inverse and forward numerical modeling of trishear fault propagation folds. Tectonics 17 (4), 640-656. Benesh, N.P., Plesch, A., Shaw, J.H., Frost, E.K., 2007. Investigation of growth fault bend folding using discrete element modeling: implications for signatures of active folding above blind thrust faults. J. Geophys. Res. 112 (B03S04) http:// dx.doi.org/10.1029/2006JB004466. Bolt, B.A. (1978), The local magnitude ML of the Kern County Earthquake of July 21, 1952, Bulletin of the Seismological Society of America, 68 (2), 513-515. Dolan, J.F., K. Sieh, T.J. Rockwell, R.S. Yeats, J. Shaw, J. Suppe, G.J. Huftile, E.M. Gath (1995), Prospects for larger or more frequent earthquakes in the Los Angeles metropolitan region, Science, 267, 199-205. Dolan, J.F., S.A. Christofferson, J.H. Shaw (2003), Recognition of paleoearthquakes on the Puente Hills blind thrust faults, California, Science, 300, 115-118. Dreger, D. and B. Savage (1999), Aftershocks of the 1952 Kern County, California, earthquake sequence: Bulletin of the Seismological Society of America, v. 89, p. 1094-1108. Field, E.H., H. A. Seligson, N. Gupta, V. Gupta, T.
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