Cross double-difference inversion for microseismic event location using data from a single monitoring well

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. KS183-KS194 ◽  
Author(s):  
Xiao Tian ◽  
Wei Zhang ◽  
Jie Zhang
Keyword(s):  
Velocity Model ◽  
P Wave ◽  
Double Difference ◽  
Separate Analysis ◽  
S Wave ◽  
Monitoring Wells ◽  
Monitoring Well ◽  
Single Well ◽  
Microseismic Events ◽  
Wave Arrival

The double-difference (DD) location method has long been applied for locating a cluster of earthquakes with data recorded at surface seismic stations. This method has also been used for locating microseismic events with multiple monitoring wells during hydraulic fracturing. We first extended the approach for locating a cluster of microseismic events with data recorded from a single well. To do this, we have reduced the 3D location problem to 2D by projecting all of the events onto a vertical ([Formula: see text]) plane, with a vertical [Formula: see text]-axis and a horizontal [Formula: see text]-axis representing the distance to the monitoring well, considering the symmetric character of the 1D velocity model and the vertical monitoring well. We then performed a 2D location inversion and projected the results back to 3D using the event azimuths, which were determined from a separate analysis of the initial P-wave polarizations. However, although the DD method could determine relative locations of events reasonably well, it yielded poor absolute locations. We have developed a cross DD (CDD) approach using the cross traveltime difference between the P-wave arrival of one event and the S-wave arrival of another event for inversion instead of the arrival-time differences of the same phases as in the DD method. The CDD method contains more information on absolute locations than the DD method, resulting in a much more stable absolute location determination. The synthetic and field data tests indicated that the CDD method could improve the accuracy of relative and absolute event locations in microseismic clusters.

Joint microseismic event location and anisotropic velocity inversion with the cross double-difference method using downhole microseismic data

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. KS63-KS73
Author(s):  
Yangyang Ma ◽  
Congcong Yuan ◽  
Jie Zhang
Keyword(s):  
Arrival Time ◽  
Velocity Model ◽  
P Wave ◽  
Double Difference ◽  
S Wave ◽  
Arrival Times ◽  
Monitoring Well ◽  
The Cross ◽  
Microseismic Event ◽  
Wave Arrival

We have applied the cross double-difference (CDD) method to simultaneously determine the microseismic event locations and five Thomsen parameters in vertically layered transversely isotropic media using data from a single vertical monitoring well. Different from the double-difference (DD) method, the CDD method uses the cross-traveltime difference between the S-wave arrival time of one event and the P-wave arrival time of another event. The CDD method can improve the accuracy of the absolute locations and maintain the accuracy of the relative locations because it contains more absolute information than the DD method. We calculate the arrival times of the qP, qSV, and SH waves with a horizontal slowness shooting algorithm. The sensitivities of the arrival times with respect to the five Thomsen parameters are derived using the slowness components. The derivations are analytical, without any weak anisotropic approximation. The input data include the cross-differential traveltimes and absolute arrival times, providing better constraints on the anisotropic parameters and event locations. The synthetic example indicates that the method can produce better event locations and anisotropic velocity model. We apply this method to the field data set acquired from a single vertical monitoring well during a hydraulic fracturing process. We further validate the anisotropic velocity model and microseismic event locations by comparing the modeled and observed waveforms. The observed S-wave splitting also supports the inverted anisotropic results.

Hypocenter Analysis of Aftershocks Data of the Mw 6.3, 27 May 2006 Yogyakarta Earthquake Using Oct-Tree Importance Sampling Method

2018 ◽  
Vol 881 ◽  
pp. 89-97 ◽  
Author(s):  
Asri Wulandari ◽  
Ade Anggraini ◽  
Wiwit Suryanto
Keyword(s):  
Importance Sampling ◽  
Sampling Method ◽  
Velocity Model ◽  
Fault Scarp ◽  
P Wave ◽  
Double Difference ◽  
S Wave ◽  
Maximum Probability ◽  
Importance Sampling Method ◽  
Dip Angle

Yogyakarta earthquake, Mw 6.3, 27 May 2006 had killed 5,571 victims and destroyed more than 1 million buildings. This incident became the most destructive earthquake disaster over the last 11 years in Indonesia. Earthquake mitigation plan in the area has been carried out by understands the location of the fault. The location of the fault is still unclear among geoscientists until now. In this case, analysis of the aftershocks using oct-tree importance sampling method was applied to support the location of the fault that responsible for the 2006 Yogyakarta earthquake. Oct-tree importance sampling is a method that is recursively subdividing the solution domain into exactly eight children for estimating properties of a particular distribution. The final result of the subdividing process is a cell that has a maximum Probability Density Function (PDF) and identified as the location of the hypocenter. Input data consists of the arrival time of the P wave and S wave of the aftershocks catalog from 3-7 June 2006 and the coordinate of the 12 seismometers, and 1D velocity model of the study area. Based on the hypocenter distribution of the aftershocks data with the proposed method show a clearer trend of the fault compared with the aftershocks distribution calculated with theHypo71program. The fault trend has a strike orientation of N 42° E with a dip angle of 80° parallel with the fault scarp along the Opak River at the distance of about 15 km to the east. This fault trend is similar with the fault orientation obtained using the Double Difference Algorithm.

Passive seismic tomography using recorded microseismicity: Application to mining-induced seismicity

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. B41-B57 ◽  
Author(s):  
Himanshu Barthwal ◽  
Mirko van der Baan
Keyword(s):  
Seismic Tomography ◽  
Velocity Model ◽  
P Wave ◽  
Double Difference ◽  
Lateral Velocity ◽  
Study Region ◽  
Arrival Times ◽  
3D Velocity Model ◽  
Passive Seismic ◽  
Dip Angle

Microseismicity is recorded during an underground mine development by a network of seven boreholes. After an initial preprocessing, 488 events are identified with a minimum of 12 P-wave arrival-time picks per event. We have developed a three-step approach for P-wave passive seismic tomography: (1) a probabilistic grid search algorithm for locating the events, (2) joint inversion for a 1D velocity model and event locations using absolute arrival times, and (3) double-difference tomography using reliable differential arrival times obtained from waveform crosscorrelation. The originally diffusive microseismic-event cloud tightens after tomography between depths of 0.45 and 0.5 km toward the center of the tunnel network. The geometry of the event clusters suggests occurrence on a planar geologic fault. The best-fitting plane has a strike of 164.7° north and dip angle of 55.0° toward the west. The study region has known faults striking in the north-northwest–south-southeast direction with a dip angle of 60°, but the relocated event clusters do not fall along any mapped fault. Based on the cluster geometry and the waveform similarity, we hypothesize that the microseismic events occur due to slips along an unmapped fault facilitated by the mining activity. The 3D velocity model we obtained from double-difference tomography indicates lateral velocity contrasts between depths of 0.4 and 0.5 km. We interpret the lateral velocity contrasts in terms of the altered rock types due to ore deposition. The known geotechnical zones in the mine indicate a good correlation with the inverted velocities. Thus, we conclude that passive seismic tomography using microseismic data could provide information beyond the excavation damaged zones and can act as an effective tool to complement geotechnical evaluations.

Scalar reverse‐time depth migration of prestack elastic seismic data

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1519-1527 ◽  
Author(s):  
Robert Sun ◽  
George A. McMechan
Keyword(s):  
Seismic Waves ◽  
Velocity Model ◽  
P Wave ◽  
Common Source ◽  
Reverse Time ◽  
S Wave ◽  
Wave Source ◽  
Reflected Waves ◽  
S Waves ◽  
Elastic Data

Reflected P‐to‐P and P‐to‐S converted seismic waves in a two‐component elastic common‐source gather generated with a P‐wave source in a two‐dimensional model can be imaged by two independent scalar reverse‐time depth migrations. The inputs to migration are pure P‐ and S‐waves that are extracted by divergence and curl calculations during (shallow) extrapolation of the elastic data recorded at the earth’s surface. For both P‐to‐P and P‐to‐S converted reflected waves, the imaging time at each point is the P‐wave traveltime from the source to that point. The extracted P‐wave is reverse‐time extrapolated and imaged with a P‐velocity model, using a finite difference solution of the scalar wave equation. The extracted S‐wave is reverse‐time extrapolated and imaged similarly, but with an S‐velocity model. Converted S‐wave data requires a polarity correction prior to migration to ensure constructive interference between data from adjacent sources. Synthetic examples show that the algorithm gives satisfactory results for laterally inhomogeneous models.

scholarly journals The potential of seismic cross-hole tomography for geotechnical site investigation

2019 ◽  
Vol 92 ◽  
pp. 18006
Author(s):  
Yannick Choy Hing Ng ◽  
William Danovan ◽  
Taeseo Ku
Keyword(s):  
Wave Velocity ◽  
Site Investigation ◽  
Velocity Model ◽  
P Wave ◽  
Reconstruction Technique ◽  
Sufficient Information ◽  
Eastern Region ◽  
S Wave ◽  
Near Surface ◽  
Soil Layers

Seismic cross-hole tomography has been commonly used in oil and gas exploration and the mining industry for the detection of precious resources. For near-surface geotechnical site investigation, this geophysical method is relatively new and can be used to supplement traditional methods such as the standard penetration test, coring and sampling, thus improving the effectiveness of site characterization. This paper presents a case study which was carried out on a reclaimed land in the Eastern region of Singapore. A seismic cross-hole test was performed by generating both compressional waves and shear waves into the ground. The signals were interpreted by using first-arrival travel time wave tomography and the arrival times were subsequently inverted using Simultaneous Iterative Reconstruction Technique (SIRT). A comparison with the borehole logging data indicated that P-wave velocity model cannot provide sufficient information about the soil layers, especially when the ground water table is near the surface. The S-wave velocity model seemed to agree quite well with the variation in the SPT-N value and could identify to a certain extent the interface between the different soil layers. Finally, P-wave and S-wave velocities are used to compute the Poisson's ratio distribution which gave a good indication of the degree of saturation of the soil.

scholarly journals Anisotropy extraction using a deviated well in the Mahanadi Basin, East Coast of India

2019 ◽  
Vol 10 (3) ◽  
pp. 911-918
Author(s):  
Biplab Kumar Mukherjee ◽  
G. Karthikeyan ◽  
Karanpal Rawat ◽  
Hari Srivastava
Keyword(s):  
Seismic Data ◽  
East Coast ◽  
Velocity Model ◽  
P Wave ◽  
S Wave ◽  
Gardner Equation ◽  
East Coast Of India ◽  
Nonlinear Fitting ◽  
Sonic Log ◽  
Mahanadi Basin

Abstract Shale is the primary rock type in the shallow marine section of the Mahanadi Basin, East Coast of India. Shale, being intrinsically anisotropic, always affects the seismic data. Anisotropy derived from seismic and VSP has lower resolution and mostly based on P wave. The workflow discussed here uses Gardner equation to derive vertical velocity and uses a nonlinear fitting to extract the Thomsen’s parameters using both the P wave and S wave data. These parameters are used to correct the sonic log of a deviated well as well as anisotropic AVO response of the reservoir. The presence of negative delta was observed, which is believed to be affected by the presence of chloride and illite in the rock matrix. This correction can be used to update the velocity model for time–depth conversion and pore pressure modelling.

Prestack 2D parsimonious Kirchhoff depth migration of elastic seismic data

Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. S157-S164 ◽  
Author(s):  
Robert Sun ◽  
George A. McMechan
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
P Wave ◽  
P Value ◽  
Common Source ◽  
S Wave ◽  
P Values ◽  
Depth Migration ◽  
Reflector Surface ◽  
Kirchhoff Depth Migration

We have extended prestack parsimonious Kirchhoff depth migration for 2D, two-component, reflected elastic seismic data for a P-wave source recorded at the earth’s surface. First, we separated the P-to-P reflected (PP-) waves and P-to-S converted (PS-) waves in an elastic common-source gather into P-wave and S-wave seismograms. Next, we estimated source-ray parameters (source p values) and receiver-ray parameters (receiver p values) for the peaks and troughs above a threshold amplitude in separated P- and S-wavefields. For each PP and PS reflection, we traced (1) a source ray in the P-velocity model in the direction of the emitted ray angle (determined by the source p value) and (2) a receiver ray in the P- or S-velocity model back in the direction of the emergent PP- or PS-wave ray angle (determined by the PP- or PS-wave receiver p value), respectively. The image-point position was adjusted from the intersection of the source and receiver rays to the point where the sum of the source time and receiver-ray time equaled the two-way traveltime. The orientation of the reflector surface was determined to satisfy Snell’s law at the intersection point. The amplitude of a P-wave (or an S-wave) was distributed over the first Fresnel zone along the reflector surface in the P- (or S-) image. Stacking over all P-images of the PP-wave common-source gathers gave the stacked P-image, and stacking over all S-images of the PS-wave common-source gathers gave the stacked S-image. Synthetic examples showed acceptable migration quality; however, the images were less complete than those produced by scalar reverse-time migration (RTM). The computing time for the 2D examples used was about 1/30 of that for scalar RTM of the same data.

Guidelines for building a detailed elastic depth model

Geophysics ◽  
2000 ◽  
Vol 65 (1) ◽  
pp. 35-45
Author(s):  
Jarrod C. Dunne ◽  
Greg Beresford ◽  
Brian L. N Kennett
Keyword(s):  
Wave Velocity ◽  
Mode Conversion ◽  
Poisson Ratio ◽  
Velocity Model ◽  
P Wave ◽  
Time Interval ◽  
S Wave ◽  
Sea Floor ◽  
P Wave Velocity ◽  
Inelastic Attenuation

We developed guidelines for building a detailed elastic depth model by using an elastic synthetic seismogram that matched both prestack and stacked marine seismic data from the Gippsland Basin (Australia). Recomputing this synthetic for systematic variations upon the depth model provided insight into how each part of the model affected the synthetic. This led to the identification of parameters in the depth model that have only a minor influence upon the synthetic and suggested methods for estimating the parameters that are important. The depth coverage of the logging run is of prime importance because highly reflective layering in the overburden can generate noise events that interfere with deeper events. A depth sampling interval of 1 m for the P-wave velocity model is a useful lower limit for modeling the transmission response and thus maintaining accuracy in the tie over a large time interval. The sea‐floor model has a strong influence on mode conversion and surface multiples and can be built using a checkshot survey or by testing different trend curves. When an S-wave velocity log is unavailable, it can be replaced using the P-wave velocity model and estimates of the Poisson ratio for each significant geological formation. Missing densities can be replaced using Gardner’s equation, although separate substitutions are required for layers known to have exceptionally high or low densities. Linear events in the elastic synthetic are sensitive to the choice of inelastic attenuation values in the water layer and sea‐floor sediments, while a simple inelastic attenuation model for the consolidated sediments is often adequate. The usefulness of a 1-D depth model is limited by misties resulting from complex 3-D structures and the validity of the measurements obtained in the logging run. The importance of such mis‐ties can be judged, and allowed for in an interpretation, by recomputing the elastic synthetic after perturbing the depth model to simulate the key uncertainties. Taking the next step beyond using simplistic modeling techniques requires extra effort to achieve a satisfactory tie to each part of a prestack seismic record. This is rewarded by the greater confidence that can then be held in the stacked synthetic tie and applications such as noise identification, data processing benchmarking, AVO analysis, and inversion.

scholarly journals Hypocenter Determination of Volcano-Tectonic (VT) Earthquake around Agung Volcano in Period October-December 2017 Using a Non-Linear Location Method: A Preliminary Result

2021 ◽  
Vol 873 (1) ◽  
pp. 012098
Author(s):  
P P Rahsetyo ◽  
D P Sahara ◽  
A D Nugraha ◽  
D K Syahbana ◽  
Zulfakriza ◽  
...  
Keyword(s):  
Volcanic Eruptions ◽  
Velocity Model ◽  
P Wave ◽  
Significant Activity ◽  
S Wave ◽  
Location Method ◽  
Hypocenter Determination ◽  
Velocity Models ◽  
Central Java ◽  
Non Linear

Abstract Agung is one of active volcanoes in Indonesia, located on island of Bali. Since 1963, Agung has not had significant activity, until in September 2017 the volcano was active again which was marked by increased seismic activity and eruptions in November 2017. Therefore, to analyze the dynamics and processes of active volcanic eruptions requires an understanding of the structure of the volcano, especially the position of the magma reservoir and its path. The depiction of the structure of this volcano can be analyzed by determining the location of the earthquake due to volcanic activity, especially Volcano-Tectonic (VT) earthquake. In this study, we determined the location of the hypocenter around the Agung using the non-linear location method. VT earthquakes have similar characteristics to tectonic earthquakes so this method can be used to determine the initial hypocenter. The data used in this study came from 8 PVMBG seismographs from October to December 2017. We manually picking arrival time of P- and S-waves from the 3948 VT events found. Pair of P and S wave phases with 18741 P-wave phases and 17237 S-wave phases, plotted in a wadati diagram resulting in a vp/vs ratio of 1.7117. We use 1D velocity models derived from Koulakov with the assumption that the geology of the study area is not much different from the volcanoes in Central Java. The resulting hypocenter distribution shows a very random location and has uncertain X, Y, and Z directions from a range of 0 to 91 km. This study limits this uncertainty to 5 km resulting in a more reliable earthquakes distribution of 3050 events. The results indicate 2 clustered events, a swarm of VT events that occur every month at a depth of 8 to 15 km and there are 2 paths that lead to the top of Agung and SW of that swarm. These preliminary results will be used to update 1D velocity model and relocate the events beneath Agung region for further studies.

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