Microseismic image-domain velocity inversion: Marcellus Shale case study

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. KS99-KS112 ◽  
Author(s):  
Ben Witten ◽  
Jeffrey Shragge
Keyword(s):  
Marcellus Shale ◽  
Velocity Variation ◽  
Signal To Noise ◽  
Injection Wells ◽  
Hydraulic Stimulation ◽  
Image Domain ◽  
Velocity Inversion ◽  
Velocity Models ◽  
Adjoint State ◽  
Event Location

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.

Image-domain velocity inversion and event location for microseismic monitoring

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. KS71-KS83 ◽  
Author(s):  
Ben Witten ◽  
Jeffrey Shragge
Keyword(s):  
Oil And Gas ◽  
Random Noise ◽  
Microseismic Monitoring ◽  
Seismic Events ◽  
S Wave ◽  
Origin Time ◽  
Image Domain ◽  
Velocity Inversion ◽  
Velocity Models ◽  
Event Location

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.

Signal-to-noise estimates of time-reverse images

Geophysics ◽  
2011 ◽  
Vol 76 (2) ◽  
pp. MA1-MA10 ◽  
Author(s):  
Ben Witten ◽  
Brad Artman
Keyword(s):  
Energy Content ◽  
Signal To Noise Ratio ◽  
Imaging Techniques ◽  
Low Frequency ◽  
Velocity Model ◽  
Noise Model ◽  
Signal To Noise ◽  
Image Domain ◽  
Velocity Models ◽  
Confidence Threshold

Locating subsurface sources from passive seismic recordings is difficult when attempted with data that have no observable arrivals and/or a low signal-to-noise ratio (S/N). Energy can be focused at its source using time-reversal techniques. However, when a focus cannot be matched to a particular event, it can be difficult to distinguish true focusing from artifacts. Artificial focusing can arise from numerous causes, including noise contamination, acquisition geometry, and velocity model effects. We present a method that reduces the ambiguity of the results by creating an estimate of the (S/N) in the image domain and defining a statistical confidence threshold for features in the images. To do so, time-reverse imaging techniques are implemented on both recorded data and a noise model. In the data domain, the noise model approximates the energy of local noise sources. After imaging, the result also captures the effects of acquisition geometry and the velocity model. The signal image is then divided by the noise image to produce an estimate of the (S/N). The distribution of image (S/N) values due to purely stochastic noise provides a means by which to calculate a confidence threshold. This threshold is used to set the minimum displayed value of images to a statistically significant limit. Two-dimensional synthetic examples show the effectiveness of this technique under varying amounts of noise and despite challenging velocity models. Using this method, we collocate anomalous low-frequency energy content, measured over oil reservoirs in Africa and Europe, with the subsurface location of the productive intervals through 2D and 3D implementations.

The relationship between Vs, Vp, density and depth based on PS-logging data at K-NET and KiK-net sites

2021 ◽  
Author(s):  
Fumiaki Nagashima ◽  
Hiroshi Kawase
Keyword(s):  
Standard Deviation ◽  
Seismic Velocity ◽  
Saturated Soil ◽  
P Wave ◽  
Soil Types ◽  
Depth Range ◽  
Velocity Inversion ◽  
Velocity Models ◽  
Regression Curves ◽  
Ps Logging

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.

scholarly journals Horizontal contraction in image domain for velocity inversion

Geophysics ◽  
2015 ◽  
Vol 80 (3) ◽  
pp. R95-R110 ◽  
Author(s):  
Peng Shen ◽  
William W. Symes
Keyword(s):  
Image Domain ◽  
Velocity Inversion

scholarly journals The 11 October 2010 Novaya Zemlya Earthquake: Implications for Velocity Models and Regional Event Location

2016 ◽  
Vol 106 (4) ◽  
pp. 1470-1481 ◽  
Author(s):  
S. J. Gibbons ◽  
G. Antonovskaya ◽  
V. Asming ◽  
Y. V. Konechnaya ◽  
E. Kremenetskaya ◽  
...  
Keyword(s):  
Novaya Zemlya ◽  
Velocity Models ◽  
Event Location

scholarly journals The 11 October 2010 Novaya Zemlya Earthquake: Implications for Velocity Models and Regional Event Location

2017 ◽  
Author(s):  
Steven Gibbons ◽  
Galina Antonovskaya ◽  
Vladimir Asming ◽  
Yana Konechnaya ◽  
Lene Kremenetskaya ◽  
...  
Keyword(s):  
Novaya Zemlya ◽  
Velocity Models ◽  
Event Location

scholarly journals Microseismic hydraulic fracture imaging in the Marcellus Shale using head waves

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. KS1-KS10 ◽  
Author(s):  
Zhishuai Zhang ◽  
James W. Rector ◽  
Michael J. Nava
Keyword(s):  
Marcellus Shale ◽  
P Wave ◽  
Head Wave ◽  
Wave Polarization ◽  
Horizontal Section ◽  
Location Accuracy ◽  
Arrival Times ◽  
Microseismic Data ◽  
Head Waves ◽  
Event Location

We have studied microseismic data acquired from a geophone array deployed in the horizontal section of a well drilled in the Marcellus Shale near Susquehanna County, Pennsylvania. Head waves were used to improve event location accuracy as a substitution for the traditional P-wave polarization method. We identified that resonances due to poor geophone-to-borehole coupling hinder arrival-time picking and contaminate the microseismic data spectrum. The traditional method had substantially greater uncertainty in our data due to the large uncertainty in P-wave polarization direction estimation. We also identified the existence of prominent head waves in some of the data. These head waves are refractions from the interface between the Marcellus Shale and the underlying Onondaga Formation. The source location accuracy of the microseismic events can be significantly improved by using the P-, S-wave direct arrival times and the head wave arrival times. Based on the improvement, we have developed a new acquisition geometry and strategy that uses head waves to improve event location accuracy and reduce acquisition cost in situations such as the one encountered in our study.

Results of the downhole microseismic monitoring at a pilot hydraulic fracturing site in Poland — Part 1: Event location and stimulation performance

2018 ◽  
Vol 6 (3) ◽  
pp. SH39-SH48 ◽  
Author(s):  
Wojciech Gajek ◽  
Jacek Trojanowski ◽  
Michał Malinowski ◽  
Marek Jarosiński ◽  
Marko Riedel
Keyword(s):  
Hydraulic Fracturing ◽  
Seismic Anisotropy ◽  
Transverse Isotropy ◽  
Velocity Model ◽  
Microseismic Monitoring ◽  
Baltic Basin ◽  
Hydraulic Stimulation ◽  
Lower Paleozoic ◽  
Event Location ◽  
Microseismic Events

A precise velocity model is necessary to obtain reliable locations of microseismic events, which provide information about the effectiveness of the hydraulic stimulation. Seismic anisotropy plays an important role in microseismic event location by imposing the dependency between wave velocities and its propagation direction. Building an anisotropic velocity model that accounts for that effect allows for more accurate location of microseismic events. We have used downhole microseismic records from a pilot hydraulic fracturing experiment in Lower-Paleozoic shale gas play in the Baltic Basin, Northern Poland, to obtain accurate microseismic events locations. We have developed a workflow for a vertical transverse isotropy velocity model construction when facing a challenging absence of horizontally polarized S-waves in perforation shot data, which carry information about Thomsen’s [Formula: see text] parameter and provide valuable constraints for locating microseismic events. We extract effective [Formula: see text], [Formula: see text] and [Formula: see text], [Formula: see text] for each layer from the P- and SV-wave arrivals of perforation shots, whereas the unresolved [Formula: see text] is retrieved afterward from the SH-SV-wave delay time of selected microseismic events. An inverted velocity model provides more reliable location of microseismic events, which then becomes an essential input for evaluating the hydraulic stimulation job effectiveness in the geomechanical context. We evaluate the influence of the preexisting fracture sets and obliquity between the borehole trajectory and principal horizontal stress direction on the hydraulic treatment performance. The fracturing fluid migrates to previously fractured zones, while the growth of the microseismic volume in consecutive stages is caused by increased penetration of the above-lying lithologic formations.

New insights into structure and seismicity of the Central Alps from 3D Pg and Sg tomography and improved hypocenter relocations

2021 ◽  
Author(s):  
Tobias Diehl ◽  
Edi Kissling ◽  
Marco Herwegh ◽  
Stefan Schmid
Keyword(s):  
Velocity Structure ◽  
Focal Depth ◽  
Small Scale ◽  
Earthquake Catalog ◽  
Depth Range ◽  
Central Alps ◽  
Quartz Content ◽  
Phase Selection ◽  
Velocity Inversion ◽  
Velocity Models

<p>Accuracy of hypocenter location, in particular focal depth, is a precondition for high-resolution seismotectonic analysis of natural and induced seismicity. For instance, linking seismicity with mapped fault segments requires hypocenter accuracy at the sub-kilometer scale. In this study, we demonstrate that inaccurate velocity models and improper phase selection can bias absolute hypocenter locations and location uncertainties, resulting in errors larger than the targeted accuracy. To avoid such bias in densely instrumented seismic networks, we propose a coupled hypocenter-velocity inversion restricted to direct, upper-crustal Pg and Sg phases. The derived three-dimensional velocity models, combined with dynamic phase selection and non-linear location algorithms result in a highly accurate earthquake catalog, including consistent hypocenter uncertainties. We apply this procedure to about 60’000 Pg and 30’000 Sg quality-checked phases of local earthquakes in the Central Alps region. The derived tomographic models image the Vp and Vs velocity structure of the Central Alps’ upper crust at unprecedented resolution, including small-scale anomalies such as those caused by a Permo-Carboniferous trough in the northern foreland, Subalpine Molasse below the Alpine front or crystalline basement units within the Penninic nappes. The external Aar Massif is characterized by low Vp/Vs ratios of about 1.625-1.675 in the depth range of 2-6.5 km, which we relate to a felsic composition of the uplifted crustal block, possibly with increased quartz content. Finally, we discuss along-strike variations imaged by relocated seismicity in the Central Alps and demonstrate how joint interpretation of velocity structure and hypocenters provides additional constraints on lithologies of upper-crustal seismicity.</p>

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