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Assembling So. Nevada Geophysical Data to Model Seismic Response in Las Vegas Valley John N. Louie & John G. Anderson Seismological Lab, UNR May 2002 -

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Presentation on theme: "Assembling So. Nevada Geophysical Data to Model Seismic Response in Las Vegas Valley John N. Louie & John G. Anderson Seismological Lab, UNR May 2002 -"— Presentation transcript:

1 Assembling So. Nevada Geophysical Data to Model Seismic Response in Las Vegas Valley John N. Louie & John G. Anderson Seismological Lab, UNR May May 2005

2 J. LLNL 10/22/2004 LVVSR  Model Assembler Enables LLNL to use existing knowledgeEnables LLNL to use existing knowledge Adding new data; interoperation and archivingAdding new data; interoperation and archiving  Shallow shear-velocity transects Extensive reconnaissance dataExtensive reconnaissance data  E3D sensitivity studies Place facilities and expertise at UNRPlace facilities and expertise at UNR Guide model assemblyGuide model assembly

3 J. LLNL 10/22/2004  A code to stitch together existing regional geophysical and geological data sets.  Generates multi- gigabyte E3D input. Model Assembler

4 J. LLNL 10/22/2004 Jachens, 1999 GB Classified Geology

5 J. LLNL 10/22/2004 Regional Basin Depths Jachens and Blakely, USGS Sedimentary and Volcanic Derived from Basin Gravity

6 J. LLNL 10/22/2004 Model Assembler stitches together Langenheims’s thickness model for the Las Vegas basin, and basin depths estimated by a bedrock proximity rule from a geologic map of the southwestern US. Map views of vertically averaged velocities in the Vp output of MA are made with the JRG tool. Precedence Rule

7 J. LLNL 10/22/2004 Minimum Basin Thickness Test ModelAssembler interpolates basin depth data by distance-weighted averaging of all data points within a radius of the grid point. (Here the radius was 1 km.) So bedrock areas within a radius of a basin point can receive small thicknesses. A minimum basin thickness rule controls the area of bedrock after interpolation. There is no effect on proximity basin-depth estimates. Interpolation Rule

8 J. LLNL 10/22/2004 Comparison of Regional Basin Estimators Rogers’s March ‘02 5% topographic gradient result is above. Bedrock is blue and basins are yellow. (Only showing surface velocity.) Louie’s July ‘02 ModelAssembler 2.0 result is below. Bedrock is red and basins are green-to-blue. (Showing 20-km vertical velocity average.) The bedrock nature of flat Pahute Mesa is now shown, but some Tertiary sediments like the Funeral Fm. in Death Valley also show as bedrock. LV SM PM PM DV DV

9 J. LLNL 10/22/2004 Model Assembler Operation Outline   Documents the methods in MA  An outline in place of a complicated flowchart. Guidance to users in this color.  Guidance to users in this color.

10 J. LLNL 10/22/ Self-document and get infile name from command line  Usage: java ModelAssembler file.in > file.out  Run from UNIX command line.  The infile is a control file, in a format identical to that used by E3D, containing additional control lines ignored by E3D. MA reads its additional lines and several E3D control lines. MA acts as a preprocessor for E3D by helping to set up the E3D control file as well as the multi-Gb grid inputs for E3D.  MA acts as a preprocessor for E3D by helping to set up the E3D control file as well as the multi-Gb grid inputs for E3D. 2.Read infile to a Vector of Strings, one per line  Vector input = ModelAssembler.readInput(infile);  The infile (control file) is simply read into a series of strings, one per line, including all comments and lines for E3D ignored by MA. Model Assembler Operation Outline

11 J. LLNL 10/22/ Parse input Vector to set up grid class with parameters  Grid grid = new Grid(input);  The infile strings are parsed to identify the unique “grid” control line, which sets the geographic location, orientation, and sampling of the 3-d grid.  The translation between lat and lon and grid coordinates uses a flat-earth Cartesian projection accurate only at the midpoint of the grid. Grid axes follow rhumb lines and not great circles. 4.Parse input Vector to set up needed classes and parameters, and read data files, producing ordered precedence Vector of class Fill objects  grid.preced = Fill.setupInput(grid, input);  Parses basin and geotech lines from control file. Based on order of basin and geotech lines in control file, arranges which detailed data sets will substitute for (take precedence over) regional background data sets, where there is overlap.  Based on order of basin and geotech lines in control file, arranges which detailed data sets will substitute for (take precedence over) regional background data sets, where there is overlap.  Opens and reads the geological data from the files the control lines point to. Geological data are always georeferenced, and supplied to MA as editable text files with points in any order.  Geological data are always georeferenced, and supplied to MA as editable text files with points in any order. Model Assembler Operation Outline

12 J. LLNL 10/22/ Compute basin thickness at all surface points of grid  grid.setupThicks();  Interpolates basin thickness at each surface point of grid from precedence list of basin data sets.  Sorting out closest basin data points for each grid surface point from unordered data vectors is now computationally inefficient (done by brute force) and time consuming. The interpolation of basin thickness is a distance-weighted average of all basin thickness data points (not geographically superceded) falling within a radius of the grid surface point.  The interpolation of basin thickness is a distance-weighted average of all basin thickness data points (not geographically superceded) falling within a radius of the grid surface point.  A rule controls when small interpolated thicknesses are considered to be zero. The search radius for data points is a parameter set for each data set in each basin line in the control file. The radius controls the 3d effect.  The search radius for data points is a parameter set for each data set in each basin line in the control file. The radius controls the 3d effect. Where no data points are within radius, the location is assumed to be bedrock, outside any basin.  Where no data points are within radius, the location is assumed to be bedrock, outside any basin. Model Assembler Operation Outline

13 J. LLNL 10/22/ Compute geotechnical shear velocity at all surface points of grid  grid.setupGeotech();  Interpolates geotechnical shear velocity at each surface point of grid from precedence list of geotech data sets.  The interpolation of geotechnical velocities is a distance-weighted average of all geotechnical data points (not geographically superceded) falling within a radius of the grid surface point.  The search radius for data points is a parameter set for each data set in each geotech line in the control file.  Where no data points are within radius, the NEHRP B-C Boundary 30-m shear velocity of 0.76 km/s is assumed outside basins, and the NEHRP C-D Boundary 30-m shear velocity of 0.35 km/s is assumed inside basins. Model Assembler Operation Outline

14 J. LLNL 10/22/ If requested write Field (2000, 2001) amplifications for all surface points of grid  grid.writeAmplif(input);  Computed directly from interpolated basin thickness and geotechnical velocity. 8.Write binary grid files given precedence Vector  grid.writeGrids();  Interpolates grid depth-point properties from rules programmed for properties versus depth inside and outside basins.  Rules control estimation of other properties from the property set by the rule for a particular geology and depth.  Within basins, a rule sets the density-versus-depth profile (Jachens and Blakely model from oil-well logs in central Nevada); an equation estimates Vp (km/s) from density (g/cc)– {qv = density/0.23; vp = qv*qv*qv*qv*0.3048/1000);} ; and Vp/Vs is assumed to be the square root of three to estimate Vs.  Outside and under basins, a rule sets the Vp-versus-depth profile- the profile used by the SGBDSN for earthquake location; an equation (inverse of above) determines density from Vp; and then the same Vp/Vs ratio is applied.  Properties at depths between control-point depths in the rules are linearly interpolated.  Properties at depths between control-point depths in the rules are linearly interpolated.(more…) Model Assembler Operation Outline

15 J. LLNL 10/22/ (continued). Write binary grid files given precedence Vector  Geotechnical velocities are thickness-weighted and slowness-averaged into the shear velocities of the upper grid zones.  Where basin depths are less than the grid spacing dh, geotechnical, basin, and bedrock velocities are all thickness-weighted and slowness-averaged into the shear velocity of the upper grid zone.  Except in the uppermost zone, to depth dh, there is no averaging across basin boundaries. A grid zone is either all in the basin or it is all in the bedrock.  Given the pre-computed interpolated basin thicknesses and geotechnical velocities, following the profile and equation rules to compute the properties at the grid zone depths is rapid, and writing large grid volumes is not slow. All these operations could be done inside E3D. 9.Write (altered) input file to standard out  ModelAssembler.outputInput(input);  MA writes a new version of the control file for input to E3D, adding translation of lat and lon given for source and sac lines to grid l, m, n coordinates. Model Assembler Operation Outline

16 J. LLNL 10/22/2004 Illustrate Models with Field (2001) Amplification-Mapping  To visualize 1-10 km basin depths together with shallow geotechnical velocities.

17 J. LLNL 10/22/2004 How to Interpolate Randomly Spaced Measurements?  ModelAssembler does the gridding of arbitrarily located geological data. Basin thicknesses and geotechnical velocities. Basin thicknesses and geotechnical velocities. Data are geo-referenced to points on a map. Data are geo-referenced to points on a map.  MA averages and interpolates among points on a map. If grid zone contains one or more measurements, average them. If grid zone contains one or more measurements, average them. If not, extrapolate from nearby measurements. If not, extrapolate from nearby measurements. Use default properties if no data “nearby.” Use default properties if no data “nearby.”

18 J. LLNL 10/22/2004 How to Interpolate Randomly Spaced Measurements?  Assign value of nearest neighbor within search radius

19 J. LLNL 10/22/2004 How to Interpolate Randomly Spaced Measurements?

20 J. LLNL 10/22/2004 How to Interpolate Randomly Spaced Measurements?  Distance-weighted average of all within search radius

21 J. LLNL 10/22/2004 How to Interpolate Randomly Spaced Measurements?

22 J. LLNL 10/22/2004 How to Interpolate Randomly Spaced Measurements?  Distance-weighted average of closest in each quadrant

23 J. LLNL 10/22/2004 Average Nearest in Each Quadrant

24 J. LLNL 10/22/2004 Observations on Interpolations  “Nearness” radius setting has big effect. Default properties differ sharply from local data. Default properties differ sharply from local data.  Nearest-neighbor looks “geological.” May represent spatial variability, but low confidence in extrapolated values. May represent spatial variability, but low confidence in extrapolated values.  Average of all nearby data is too smooth. Misrepresents spatial variability, but gives high confidence in regional average values. Misrepresents spatial variability, but gives high confidence in regional average values. Used by MA3 for basin thickness and geotechnical data. Used by MA3 for basin thickness and geotechnical data.  Average of nearest data in 4 directions seems more realistic. Still requires making a geologic model. Retains some of the measured spatial variability. Retains some of the measured spatial variability. Extrapolating averages gives higher confidence. Extrapolating averages gives higher confidence.

25 J. LLNL 10/22/2004 Most of Strip, Downtown; south side of Valley only Las Vegas Transect Measurements

26 J. LLNL 10/22/2004 V 100 echoes V 30 Las Vegas Transect Measurements

27 J. LLNL 10/22/2004 Geologic Info to Predict V s NSL, July ‘03, sponsored by LLNL  Can soil maps predict V s ?

28 J. LLNL 10/22/2004 Does extrapolating V s work?  V s assigned to soil-map units using central-City measurements.  Later, outlying measurements (B. Luke, UNLV) not predicted by maps.

29 J. LLNL 10/22/2004 Does extrapolating V s work?  V s assigned to soil-map units using central-City measurements.  Later, outlying measurements (B. Luke, UNLV) not predicted by maps

30 J. LLNL 10/22/2004 How to Extrapolate Shallow V s  Can we simply extrapolate measurements throughout basin?  No, need guidance of a geologic model.

31 J. LLNL 10/22/2004

32 LVVSR  Model Assembler Delivery to LLNL Incorporates stratigraphic model for LVVIncorporates stratigraphic model for LVV Adjusts regional assumptions to fit LVV dataAdjusts regional assumptions to fit LVV data

33 J. LLNL 10/22/2004 How to Extrapolate Shallow V s  Correlate 75 Vs measurements against stratigraphic model.  Stratigraphy interpolated between >500 water-well logs.

34 J. LLNL 10/22/2004 Extrapolated vs. Measured  Comparisons along Cheyenne-to-Tropicana transect.

35 J. LLNL 10/22/2004 How to Extrapolate Shallow V s  With subsurface information, prediction is better than with soil map.

36 J. LLNL 10/22/2004 How to Extrapolate Shallow V s  Well-log correlations predict measurements at more sites than with soil-map correlations.  Hazard is underestimated at fewer sites.

37 J. LLNL 10/22/2004 Create Top Zone for E3D Grid  Always average on slowness.  Velocities from top 100 meters of stratigraphic model.  Deeper zones interpolate refraction results.  Revise defaults to match.

38 J. LLNL 10/22/2004 Integrate LV Results with Region

39 J. LLNL 10/22/2004 Integrate LV Results with Region

40 J. LLNL 10/22/2004Summary  Shallow Shear-Velocity Modeling Difficult to predict amplification from maps. Difficult to predict amplification from maps. Stratigraphic model now predicts measurements, extends throughout urban Valley. Stratigraphic model now predicts measurements, extends throughout urban Valley. Shallow basin has remarkably constant Vs. Shallow basin has remarkably constant Vs.  Model Assembler Interpolates point measurements. Interpolates point measurements. Averages data & models into grid. Averages data & models into grid. Incorporates stratigraphic model for shallow LVV. Incorporates stratigraphic model for shallow LVV. Regional assumptions adjusted to match LVV data. Regional assumptions adjusted to match LVV data.

41 J. LLNL 10/22/2004

42 New Deployment

43 J. LLNL 10/22/2004 MA Java-C Conversion Notes  A complete re-design of the C code, with help from Dr. Harris and Jeff Stuart  Uses void pointer and type-casting to implement a single Vector structure that is re-usable for different data types fewer files and pointers need to be handled fewer files and pointers need to be handled

44 J. LLNL 10/22/2004 Java-C Conversion  For the Vector structure: Explicit functions to allocate and release memory (for an instance of the structure) were implemented Explicit functions to allocate and release memory (for an instance of the structure) were implemented easier to check for memory leakseasier to check for memory leaks clearer and more coherent codeclearer and more coherent code

45 J. LLNL 10/22/2004 Java-C Conversion  Additional structures also have new() and delete() functions that specifically allocate and release memory easier to detect memory leaks easier to detect memory leaks  Static memory allocation is used as much as possible for the implementation of the various structures to ease the task of handling memory allocation and release to ease the task of handling memory allocation and release

46 J. LLNL 10/22/2004 Java-C Conversion  The new implementation is still a direct translation of the original java code.  For example, each “.java” file is converted into a “.h” and a “.c” file.

47 J. LLNL 10/22/2004 Speed Comparison  Testing with an Intel Pentium 4 machine with sample parameters: The C code execution finishes in about 3.5 minutes, compared to 4.5 minutes for the original Java code The C code execution finishes in about 3.5 minutes, compared to 4.5 minutes for the original Java code ~20% performance increase~20% performance increase Much additional optimization still to doMuch additional optimization still to do

48 J. LLNL 10/22/2004 Result Comparison  Testing on Mac OS10.3, the C conversion generates effectively identical binary output files (i.e., den.flt, vs.flt, vp.flt,) compared to the java code -=

49 J. LLNL 10/22/2004 Required MA4 Enhancements  Include regional geophysical grids in MA. The “grids” will be supplied as property-vs-depth profiles. The “grids” will be supplied as property-vs-depth profiles.  Alterations to the geotech operations to average in full profiles instead of the V 30 values put in now. Geotech and regional profiles in Luke’s format. Geotech and regional profiles in Luke’s format.  All averaging and interpolation of Vp and Vs done arithmetically on slowness (inverse velocity, for conservation of travel time). Densities combine arithmetically for conservation of mass. Approximate completion date: mid-May Approximate completion date: mid-May

50 J. LLNL 10/22/2004 Other MA4 Enhancements  Optional control from basin, profile, and geotech parameter lines on the type of interpolation used: nearest neighbor, linear, distance- weighted, etc. expected completion date: before mid April expected completion date: before mid April  Precision control by truncation of results to 3 or 4 significant figures, to assure identical output across platforms and compilers expected completion date: before April expected completion date: before April

51 J. LLNL 10/22/2004  ReMi measures Rayleigh dispersion with linear refraction arrays. Shallow Shear-Velocity Transects

52 J. LLNL 10/22/2004 ReMi has classified hard and soft sites around the world by measuring V 30, average shear velocity to 30 m depth. Refraction Microtremor for Shallow Shear Velocity

53 J. LLNL 10/22/2004 Transect Data High-velocity picks at >0.4 sec period are unreliable. Picks at sec illustrate velocity differences to 100 m depth.


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