Image-domain velocity inversion and event location for microseismic monitoring

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. KS71-KS83 ◽  
Author(s):  
Ben Witten ◽  
Jeffrey Shragge

Microseismic event locations obtained from seismic monitoring data sets are often a primary means of determining the success of fluid-injection programs, such as hydraulic fracturing for oil and gas extraction, geothermal projects, and wastewater injection. Event locations help the decision makers to evaluate whether operations conform to expectations or parameters need to be changed and may be used to help assess and reduce the risk of induced seismicity. However, obtaining accurate event location estimates requires an accurate velocity model, which is not available at most injection sites. Common velocity updating techniques require picking arrivals on individual seismograms. This can be problematic in microseismic monitoring, particularly for surface acquisition, due to the low signal-to-noise ratio of the arrivals. We have developed a full-wavefield adjoint-state method for locating seismic events while inverting for P- and S-wave velocity models that optimally focus multiple complementary images of recorded seismic events. This method requires neither picking nor initial estimates of event location or origin time. Because the inversion relies on (image domain) residuals that satisfy the differential semblance criterion, there is no requirement that the starting model be close to the true velocity. We determine synthetic results derived from a model with conditions similar to a field-acquisition scenario in terms of the number and spatial sampling of receivers and recorded coherent and random noise levels. The results indicate the effectiveness of the methodology by demonstrating a significantly enhanced focusing of event images and a reduction of 95% in event location error from a reasonable initial model.

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. KS99-KS112 ◽  
Author(s):  
Ben Witten ◽  
Jeffrey Shragge

Seismic monitoring at injection wells relies on generating accurate location estimates of detected (micro-) seismicity. Event location estimates assist in optimizing well and stage spacings, assessing potential hazards, and establishing causation of larger events. The largest impediment to generating accurate location estimates is an accurate velocity model. For surface-based monitoring, the model should capture 3D velocity variation, yet rarely is the laterally heterogeneous nature of the velocity field captured. Another complication for surface monitoring is that the data often suffer from low signal-to-noise levels, making velocity updating with established techniques difficult due to uncertainties in the arrival picks. We use surface-monitored field data to demonstrate that a new method requiring no arrival picking can improve microseismic locations by jointly locating events and updating 3D P- and S-wave velocity models through image-domain adjoint-state tomography. This approach creates a complementary set of images for each chosen event through wave-equation propagation and correlating combinations of P- and S-wavefield energy. The method updates the velocity models to optimize the focal consistency of the images through adjoint-state inversion. We have determined the functionality of the method using a surface array of 192 3C geophones over a hydraulic stimulation in the Marcellus Shale. Applying the proposed joint location and velocity-inversion approach significantly improves the estimated locations. To assess the event location accuracy, we have developed a new measure of inconsistency derived from the complementary images. By this measure, the location inconsistency decreases by 75%. The method has implications for improving the reliability of microseismic interpretation with low signal-to-noise data, which may increase hydrocarbon extraction efficiency and improve risk assessment from injection-related seismicity.


Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. WA95-WA103 ◽  
Author(s):  
Oscar Jarillo Michel ◽  
Ilya Tsvankin

Waveform inversion (WI), which has been extensively used in reflection seismology, could provide improved velocity models and event locations for microseismic surveys. Here, we develop an elastic WI algorithm for anisotropic media designed to estimate the 2D velocity field along with the source parameters (location, origin time, and moment tensor) from microseismic data. The gradient of the objective function is obtained with the adjoint-state method, which requires just two modeling simulations at each iteration. In the current implementation the source coordinates and velocity parameters are estimated sequentially at each stage of the inversion to minimize trade-offs and improve the convergence. Synthetic examples illustrate the accuracy of the inversion for layered VTI (transversely isotropic with a vertical symmetry axis) media, as well as the sensitivity of the velocity-analysis results to noise, the length of the receiver array, errors in the initial model, and variability in the moment tensor of the recorded events.


Solid Earth ◽  
2017 ◽  
Vol 8 (2) ◽  
pp. 531-544 ◽  
Author(s):  
Nikita Afonin ◽  
Elena Kozlovskaya ◽  
Ilmo Kukkonen ◽  

Abstract. Understanding the inner structure of seismogenic faults and their ability to reactivate is particularly important in investigating the continental intraplate seismicity regime. In our study we address this problem using analysis of local seismic events and ambient seismic noise recorded by the temporary DAFNE array in the northern Fennoscandian Shield. The main purpose of the DAFNE/FINLAND passive seismic array experiment was to characterize the present-day seismicity of the Suasselkä postglacial fault (SPGF), which was proposed as one potential target for the DAFNE (Drilling Active Faults in Northern Europe) project. The DAFNE/FINLAND array comprised an area of about 20 to 100 km and consisted of eight short-period and four broadband three-component autonomous seismic stations installed in the close vicinity of the fault area. The array recorded continuous seismic data during September 2011–May 2013. Recordings of the array have being analysed in order to identify and locate natural earthquakes from the fault area and to discriminate them from the blasts in the Kittilä gold mine. As a result, we found a number of natural seismic events originating from the fault area, which proves that the fault is still seismically active. In order to study the inner structure of the SPGF we use cross-correlation of ambient seismic noise recorded by the array. Analysis of azimuthal distribution of noise sources demonstrated that during the time interval under consideration the distribution of noise sources is close to the uniform one. The continuous data were processed in several steps including single-station data analysis, instrument response removal and time-domain stacking. The data were used to estimate empirical Green's functions between pairs of stations in the frequency band of 0.1–1 Hz and to calculate corresponding surface wave dispersion curves. The S-wave velocity models were obtained as a result of dispersion curve inversion. The results suggest that the area of the SPGF corresponds to a narrow region of low S-wave velocities surrounded by rocks with high S-wave velocities. We interpret this low-velocity region as a non-healed mechanically weak fault damage zone (FDZ) formed due to the last major earthquake that occurred after the last glaciation.


Geophysics ◽  
2020 ◽  
pp. 1-79
Author(s):  
Can Oren ◽  
Jeffrey Shragge

Accurately estimating event locations is of significant importance in microseismic investigations because this information greatly contributes to the overall success of hydraulic fracturing monitoring programs. Full-wavefield time-reverse imaging (TRI) using one or more wave-equation imaging conditions offers an effective methodology for locating surface-recorded microseismic events. To be most beneficial in microseismic monitoring programs, though, the TRI procedure requires using accurate subsurface models that account for elastic media effects. We develop a novel microseismic (extended) PS energy imaging condition that explicitly incorporates the stiffness tensor and exhibits heightened sensitivity to isotropic elastic model perturbations compared to existing imaging conditions. Numerical experiments demonstrate the sensitivity of microseismic TRI results to perturbations in P- and S-wave velocity models. Zero-lag and extended microseismic source images computed at selected subsurface locations yields useful information about 3D P- and S-wave velocity model accuracy. Thus, we assert that these image volumes potentially can serve as the input into microseismic elastic velocity model building algorithms.


Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. KS1-KS9 ◽  
Author(s):  
Oksana Zhebel ◽  
Leo Eisner

Microseismic monitoring has become a tool of choice for the development and optimization of oil and gas production from unconventional reservoirs. The primary objective of (micro) seismic monitoring includes localization of (micro) seismic events and characterization of their source mechanisms. Most seismic events are of a nonexplosive nature, and thus, there are waveform (polarity) differences among receivers. Specifically, double-couple sources represented a challenge for migration-based localization techniques. We developed and applied a new migration-type location technique combined with source mechanism inversion that allowed for constructive interference of signal in seismic waveforms. The procedure included constructing image functions by stacking the amplitudes with compensated polarity changes. The compensation weights were calculated by using moment tensor inversion. This method did not require any picking of arrivals at individual receivers, but it required receivers to be distributed in multiple azimuths and offsets. This made the technique suitable for surface or near-surface monitoring, in which a low signal-to-noise ratio (S/N) can be overcome by stacking. Furthermore, the advantage of this technique was that in addition to the position in time and space, we also determined the source mechanism. We determined with numerical tests that the proposed technique can be used for detection and location of events with S/Ns as low as 0.05 at individual (prestacked) receivers. Furthermore, we found that other source mechanism parameters such as magnitude, volumetric, or shear components of the source mechanism were not suitable for the location. Finally, we applied the proposed technique to a microseismic event of moment magnitude [Formula: see text] induced during the hydraulic fracturing treatment of a gas shale reservoir in North America.


2016 ◽  
Author(s):  
Nikita Afonin ◽  
Elena Kozlovskaya ◽  
Ilmo Kukkonen ◽  
DAFNE/FINLAND Working Group

Abstract. Understanding inner structure of seismogenic faults and their ability to reactivate is particularly important in investigating continental intraplate seismicity regime. In our study we address this problem using analysis of local seismic events and ambient seismic noise recorded by the temporary DAFNE array in northern Fennoscandian Shield. The main purpose of the DAFNE/FINLAND passive seismic array experiment was to characterize the present-day seismicity of the Suasselkä post-glacial fault (SPGF) that was proposed as one potential target for the DAFNE (Drilling Active Faults in Northern Europe) project. The DAFNE/FINLAND array comprised the area of about 20 to 100 km and consisted of 8 short-period and 4 broad-band 3-component autonomous seismic stations installed in the close vicinity of the fault area. The array recorded continuous seismic data during September, 2011–May, 2013. Recordings of the array have being analyzed in order to identify and locate natural earthquakes from the fault area and to discriminate them from the blasts in the Kittilä Gold Mine. As a result, we found several dozens of natural seismic events originating from the fault area, which proves that the fault is still seismically active. In order to study the inner structure of the SPGF we use cross-correlation of ambient seismic noise recorded by the array. Analysis of azimuthal distribution of noise sources demonstrated that during the time interval under consideration the distribution of noise sources is close to the uniform one. The continuous data were processed in several steps including single station data analysis, instrument response removal and time-domain stacking. The data were used to estimate empirical Green’s functions between pairs of stations in the frequency band of 0.1–1 Hz and to calculate correspondent surface wave dispersion curves. The S-wave velocity models were obtained as a result of dispersion curves inversion. The results suggest that the area of the SPGF corresponds to a narrow region of low S-wave velocities surrounded by rocks with high S-wave velocities. We interpret this low velocity region as a non-healed mechanically weak fault damage zone (FDZ) that remained after the last major earthquake that occurred after the last glaciation.


2021 ◽  
Vol 2 ◽  
Author(s):  
Saptarshi Das ◽  
Michael P. Hobson ◽  
Farhan Feroz ◽  
Xi Chen ◽  
Suhas Phadke ◽  
...  

Abstract In passive seismic and microseismic monitoring, identifying and characterizing events in a strong noisy background is a challenging task. Most of the established methods for geophysical inversion are likely to yield many false event detections. The most advanced of these schemes require thousands of computationally demanding forward elastic-wave propagation simulations. Here we train and use an ensemble of Gaussian process surrogate meta-models, or proxy emulators, to accelerate the generation of accurate template seismograms from random microseismic event locations. In the presence of multiple microseismic events occurring at different spatial locations with arbitrary amplitude and origin time, and in the presence of noise, an inference algorithm needs to navigate an objective function or likelihood landscape of highly complex shape, perhaps with multiple modes and narrow curving degeneracies. This is a challenging computational task even for state-of-the-art Bayesian sampling algorithms. In this paper, we propose a novel method for detecting multiple microseismic events in a strong noise background using Bayesian inference, in particular, the Multimodal Nested Sampling (MultiNest) algorithm. The method not only provides the posterior samples for the 5D spatio-temporal-amplitude inference for the real microseismic events, by inverting the seismic traces in multiple surface receivers, but also computes the Bayesian evidence or the marginal likelihood that permits hypothesis testing for discriminating true vs. false event detection.


Geophysics ◽  
2021 ◽  
pp. 1-92
Author(s):  
Xingda Jiang ◽  
Wei Zhang ◽  
Hui Yang ◽  
Chaofeng Zhao ◽  
Zixuan Wang

In downhole microseismic monitoring, the velocity model plays a vital role in accurate mapping of the hydraulic fracturing image. For velocity model uncertainties in the number of layers or interface depths, the conventional velocity calibration method has been shown to effectively locate the perforation shots; however, it introduces non-negligible location errors for microseismic events, especially for complex geological formations with inclinations. To improve the event location accuracy, we exploit the advantages of the reversible jump Markov chain Monte Carlo (rjMCMC) approach in generating different dimensions of velocity models and propose a transdimensional Bayesian simultaneous inversion framework for obtaining the effective velocity structure and event locations simultaneously. The transdimensional inversion changes the number of layers during the inversion process and selects the optimal interface depths and velocity values to improve the event location accuracy. The confidence intervals of the simultaneous inversion event locations estimated by Bayesian inference enable us to evaluate the location uncertainties in the horizontal and vertical directions. Two synthetic examples and a field test are presented to illustrate the performance of our methodology, and the event location accuracy is shown to be higher than that obtained using the conventional methods. With less dependence on prior information, the proposed transdimensional simultaneous inversion method can be used to obtain an effective velocity structure for facilitating highly accurate hydraulic fracturing mapping.


Author(s):  
Fumiaki Nagashima ◽  
Hiroshi Kawase

Summary P-wave velocity (Vp) is an important parameter for constructing seismic velocity models of the subsurface structures by using microtremors and earthquake ground motions or any other geophysical exploration data. In order to reflect the ground survey information in Japan to the Vp structure, we investigated the relationships among Vs, Vp, and depth by using PS-logging data at all K-NET and KiK-net sites. Vp values are concentrated at around 500 m/s and 1,500 m/s when Vs is lower than 1,000 m/s, where these concentrated areas show two distinctive characteristics of unsaturated and saturated soil, respectively. Many Vp values in the layer shallower than 4 m are around 500 m/s, which suggests the dominance of unsaturated soil, while many Vp values in the layer deeper than 4 m are larger than 1,500 m/s, which suggests the dominance of saturated soil there. We also investigated those relationships for different soil types at K-NET sites. Although each soil type has its own depth range, all soil types show similar relationships among Vs, Vp, and depth. Then, considering the depth profile of Vp, we divided the dataset into two by the depth, which is shallower or deeper than 4 m, and calculated the geometrical mean of Vp and the geometrical standard deviation in every Vs bins of 200 m/s. Finally, we obtained the regression curves for the average and standard deviation of Vp estimated from Vs to get the Vp conversion functions from Vs, which can be applied to a wide Vs range. We also obtained the regression curves for two datasets with Vp lower and higher than 1,200 m/s. These regression curves can be applied when the groundwater level is known. In addition, we obtained the regression curves for density from Vs or Vp. An example of the application for those relationships in the velocity inversion is shown.


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