Calibration of Local Magnitude Scale for Colombia

2020 ◽  
Vol 110 (4) ◽  
pp. 1971-1981
Author(s):  
Camilo Muñoz Lopez ◽  
Laura Velasquez ◽  
Viviana Dionicio

ABSTRACT New calibration for local magnitude (ML) was performed for Colombia. The territory was divided into five zones using reported attenuation values for different areas of the country and correlating this information with the mapped lithologies, the absence or presence of volcanic activity, and patterns in the hypocentral locations of seismicity. Seismic data from the Colombian National Seismic Network—Colombian Geological Survey (RSNC-SGC) were used to obtain a total of 81,232 peak amplitudes from 22,816 earthquakes recorded between January 2015 and August 2017. This set of data was incorporated into a linear inversion to calculate the distance-correction functions for each zone. A new methodology is proposed for calculating the base level of the distance-correction function or parameter c, using the amplitude values for earthquakes with moment magnitudes (Mw) close to 3 measured at stations at distances close to 100 km. The distance-correction logA0 functions obtained in this study for the five zones are: Zone  1:−logA0=1.245×log(r)+0.0024×r−2.051,Zone  2:−logA0=1.056×log(r)+0.0021×r−1.76,Zone  3:−logA0=1.07×log(r)+0.0013×r−1.531,Zone  4:−logA0=1.241×log(r)+0.0015×r−2.178,Zone  5:−logA0=0.711×log(r)+0.0009×r−0.69, in which r is the hypocentral distance in kilometers. The results of this study are in use in the RSNC-SGC since September 2018. Before using the equations presented here, the values of local magnitude were previously underestimated for the entire Colombian territory. This work allows the calculation of the local magnitude using the largest attenuation changes in addition to decreasing discrepancies with other magnitude types such as Mw and those calculated by international networks.

1987 ◽  
Vol 77 (6) ◽  
pp. 2074-2094
Author(s):  
L. K. Hutton ◽  
David M. Boore

Abstract Measurements (9,941) of peak amplitudes on Wood-Anderson instruments (or simulated Wood-Anderson instruments) in the Southern California Seismographic Network for 972 earthquakes, primarily located in southern California, were studied with the aim of determining a new distance correction curve for use in determining the local magnitude, ML. Events in the Mammoth Lakes area were found to give an unusual attenuation pattern and were excluded from the analysis, as were readings from any one earthquake at distances beyond the first occurrence of amplitudes less than 0.3 mm. The remaining 7,355 amplitudes from 814 earthquakes yielded the following equation for ML distance correction, log A0 − log A 0 = 1.110 log ( r / 100 ) + 0.00189 ( r − 100 ) + 3.0 where r is hypocentral distance in kilometers. A new set of station corrections was also determined from the analysis. The standard deviation of the ML residuals obtained by using this curve and the station corrections was 0.21. The data used to derive the equation came from earthquakes with hypocentral distances ranging from about 10 to 700 km and focal depths down to 20 km (with most depths less than 10 km). The log A0 values from this equation are similar to the standard values listed in Richter (1958) for 50 < r < 200 km (in accordance with the definition of ML, the log A0 value for r = 100 km was constrained to equal his value). The Wood-Anderson amplitudes decay less rapidly, however, than implied by Richter's correction. Because of this, the routinely determined magnitudes have been too low for nearby stations (r < 50 km) and too high for distant stations (r > 200 km). The effect at close distances is consistent with that found in several other studies, and is simply due to a difference in the observed ≈ 1/r geometrical spreading for body waves and the 1/r2 spreading assumed by Gutenberg and Richter in the construction of the log A0 table. ML's computed from our curve and those reported in the Caltech catalog show a systematic dependence on magnitude: small earthquakes have larger magnitudes than in the catalog and large earthquakes have smaller magnitudes (by as much as 0.6 units). To a large extent, these systematic differences are due to the nonuniform distribution of data in magnitude-distance space (small earthquakes are preferentially recorded at close distances relative to large earthquakes). For large earthquakes, however, the difference in the two magnitudes is not solely due to the new correction for attenuation; magnitudes computed using Richter's log A0 curve are also low relative to the catalog values. The differences in that case may be due to subjective judgment on the part of those determining the catalog magnitudes, the use of data other than the Caltech Wood-Anderson seismographs, the use of different station corrections, or the use of teleseismic magnitude determinations. Whatever their cause, the departures at large magnitude may explain a 1.0:0.7 proportionality found by Luco (1982) between ML's determined from real Wood-Anderson records and those from records synthesized from strong-motion instruments. If it were not for the biases in reported magnitudes, Luco's finding would imply a magnitude-dependent shape in the attenuation curves. We studied residuals in three magnitude classes (2.0 < ML ≦ 3.5, 3.5 < ML ≦ 5.5, and 5.5 < ML ≦ 7.0) and found no support for such a magnitude dependence. Based on our results, we propose that local magnitude scales be defined such that ML = 3 correspond to 10 mm of motion on a Wood-Anderson instrument at 17 km hypocentral distance, rather than 1 mm of motion at 100 km. This is consistent with the original definition of magnitude in southern California and will allow more meaningful comparison of earthquakes in regions having very different attenuation of waves within the first 100 km.


2020 ◽  
Vol 91 (6) ◽  
pp. 3223-3235
Author(s):  
Florentia Kavoura ◽  
Alexandros Savvaidis ◽  
Ellen Rathje

Abstract In this study, we present a local magnitude (ML) relation for the earthquakes recorded from the Texas Seismological Network (TexNet) between the dates of 1 January 2017 and 31 July 2019. Using a comprehensive seismic dataset from earthquakes in Texas, we propose a distance correction term −logA0, which is consistent with the original definition of the Richter magnitude. The proposed distance correction calculation for the TexNet events accounts for the attenuation characteristics of the direct and refracted waves over different distance ranges. Regression analysis of Wood–Anderson amplitudes results in the following trilinear function, which represents the attenuation attributes of the events under investigation: −logA0={2.07×log(Rhyp)+0.0002×(Rhyp−100)−0.72Rhyp≤16  km1.54×log(Rhyp)+0.0002×(Rhyp−100)−0.0816  km<Rhyp≤105  km,0.29×log(Rhyp)+0.0002×(Rhyp−100)+2.45Rhyp>105  km in which Rhyp is the hypocentral distance (km). The derived distance correction relationship results in an accurate ML relationship for Texas that is unbiased over a 200 km distance range. Compared with other ML relations, the proposed relation in this study gives lower ML values over all distances than those calculated by Richter (1958), Hutton and Boore (1987), Babaie Mahani and Kao (2019), and Quinones et al. (2019) by an average of 0.01, 0.12, 0.16, and 0.15 units, respectively; this study’s proposed relation gives higher ML values over all distances than those calculated by Scales et al. (2017), Yenier (2017), and Greig et al. (2018) by an average of 0.28, 0.01, and 0.08 units, respectively.


2021 ◽  
Vol 14 (3) ◽  
Author(s):  
Ali K. Abdelfattah ◽  
Abdullah Al-amri ◽  
Kamal Abdelrahman ◽  
Muhamed Fnais ◽  
Saleh Qaysi

AbstractIn this study, attenuation relationships are proposed to more accurately predict ground motions in the southernmost part of the Arabian Shield in the Jazan Region of Saudi Arabia. A data set composed of 72 earthquakes, with normal to strike-slip focal mechanisms over a local magnitude range of 2.0–5.1 and a distance range of 5–200 km, was used to investigate the predictive attenuation relationship of the peak ground motion as a function of the hypocentral distance and local magnitude. To obtain the space parameters of the empirical relationships, non-linear regression was performed over a hypocentral distance range of 4–200 km. The means of 638 peak ground acceleration (PGA) and peak ground velocity (PGV) values calculated from the records of the horizontal components were used to derive the predictive relationships of the earthquake ground motions. The relationships accounted for the site-correlation coefficient but not for the earthquake source implications. The derived predictive attenuation relationships for PGV and PGA are$$ {\log}_{10}(PGV)=-1.05+0.65\cdotp {M}_L-0.66\cdotp {\log}_{10}(r)-0.04\cdotp r, $$ log 10 PGV = − 1.05 + 0.65 · M L − 0.66 · log 10 r − 0.04 · r , $$ {\log}_{10}(PGA)=-1.36+0.85\cdotp {M}_L-0.85\cdotp {\log}_{10}(r)-0.005\cdotp r, $$ log 10 PGA = − 1.36 + 0.85 · M L − 0.85 · log 10 r − 0.005 · r , respectively. These new relationships were compared to the grand-motion prediction equation published for western Saudi Arabia and indicate good agreement with the only data set of observed ground motions available for an ML 4.9 earthquake that occurred in 2014 in southwestern Saudi Arabia, implying that the developed relationship can be used to generate earthquake shaking maps within a few minutes of the event based on prior information on magnitudes and hypocentral distances taking into considerations the local site characteristics.


Author(s):  
James Holt ◽  
James C. Pechmann ◽  
Keith D. Koper

ABSTRACT The Yellowstone volcanic region is one of the most seismically active areas in the western United States. Assigning magnitudes (M) to Yellowstone earthquakes is a critical component of monitoring this geologically dynamic zone. The University of Utah Seismograph Stations (UUSS) has assigned M to 46,767 earthquakes in Yellowstone that occurred between 1 January 1984 and 31 December 2020. Here, we recalibrate the local magnitude (ML) distance and station corrections for the Yellowstone volcanic region. This revision takes advantage of the large catalog of earthquakes and an increase in broadband stations installed by the UUSS since the last ML update in 2007. Using a nonparametric method, we invert 7728 high-quality, analyst-reviewed amplitude measurements from 1383 spatially distributed earthquakes for 39 distance corrections and 20 station corrections. The inversion is constrained with four moment magnitude (Mw) values determined from time-domain inversion of regional-distance broadband waveforms by the UUSS. Overall, the new distance corrections indicate relatively high attenuation of amplitudes with distance. The distance corrections decrease with hypocentral distance from 3 km to a local minimum at 80 km, rise to a broad peak at 110 km, and then decrease again out to 180 km. The broad peak may result from superposition of direct arrivals with near-critical Moho reflections. Our ML inversion doubles the number of stations with ML corrections in and near the Yellowstone volcanic region. We estimate that the additional station corrections will nearly triple the number of Yellowstone earthquakes that can be assigned an ML. The new ML distance and station corrections will also reduce uncertainties in the mean MLs for Yellowstone earthquakes. The new MLs are ∼0.07 (±0.18) magnitude units smaller than the previous MLs and have better agreement with 12 Mws (3.15–4.49) determined by the UUSS and Saint Louis University.


Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. N15-N27 ◽  
Author(s):  
Carlos A. M. Assis ◽  
Henrique B. Santos ◽  
Jörg Schleicher

Acoustic impedance (AI) is a widely used seismic attribute in stratigraphic interpretation. Because of the frequency-band-limited nature of seismic data, seismic amplitude inversion cannot determine AI itself, but it can only provide an estimate of its variations, the relative AI (RAI). We have revisited and compared two alternative methods to transform stacked seismic data into RAI. One is colored inversion (CI), which requires well-log information, and the other is linear inversion (LI), which requires knowledge of the seismic source wavelet. We start by formulating the two approaches in a theoretically comparable manner. This allows us to conclude that both procedures are theoretically equivalent. We proceed to check whether the use of the CI results as the initial solution for LI can improve the RAI estimation. In our experiments, combining CI and LI cannot provide superior RAI results to those produced by each approach applied individually. Then, we analyze the LI performance with two distinct solvers for the associated linear system. Moreover, we investigate the sensitivity of both methods regarding the frequency content present in synthetic data. The numerical tests using the Marmousi2 model demonstrate that the CI and LI techniques can provide an RAI estimate of similar accuracy. A field-data example confirms the analysis using synthetic-data experiments. Our investigations confirm the theoretical and practical similarities of CI and LI regardless of the numerical strategy used in LI. An important result of our tests is that an increase in the low-frequency gap in the data leads to slightly deteriorated CI quality. In this case, LI required more iterations for the conjugate-gradient least-squares solver, but the final results were not much affected. Both methodologies provided interesting RAI profiles compared with well-log data, at low computational cost and with a simple parameterization.


Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. R41-R53
Author(s):  
Yijie Zhou ◽  
Franklin Ruiz ◽  
Yequan Chen ◽  
Fan Xia

Seismic derivable elastic attributes, e.g., elastic impedance, lambda-rho, mu-rho, and Poisson impedance (PI), are routinely being used for reservoir characterization practice. These attributes could be derived from inverted [Formula: see text], [Formula: see text], and density, and usually indicate high sensitivity to reservoir lithology and fluid. Due to the high sensitivity of such elastic attributes, errors or measurement noise associated with the acquisition, processing, and inversion of prestack seismic data will propagate through the inversion products, and will lead to even larger errors in the computed attributes. To solve this problem, we have developed a two-step cascade workflow that combines linear inversion and nonlinear optimization techniques for the improved estimation of elastic attributes and better prediction and delineation of reservoir lithology and fluids. The linear inversion in the first step is an inversion scheme with a sparseness assumption, based on L1-norm regularization. This step is used to select the major reflective layer locations, followed in the second step by a nonlinear optimization process with the predefined layer structure. The combination of these two procedures produces a reasonable blocky earth model with consistent elastic properties, including the ones that are sensitive to reservoir lithology and fluid change, and thus provides an accurate approach for seismic reservoir characterization. Using PI, as one of the target elastic attributes, as an example, this workflow has been successfully applied to synthetic and field data examples. The results indicate that our workflow improves the estimation of elastic attributes from the noisy prestack seismic data and may be used for the identification of the reservoir lithology and fluid.


2006 ◽  
Author(s):  
C. H. Lam ◽  
S. Bakrac ◽  
P. M. van den Berg ◽  
A. Gisolf

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