scholarly journals The shallow structure of Mars at the InSight landing site from inversion of ambient vibrations

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
M. Hobiger ◽  
M. Hallo ◽  
C. Schmelzbach ◽  
S. C. Stähler ◽  
D. Fäh ◽  
...  
Keyword(s):  
Seismic Data ◽  
Seismic Velocity ◽  
Landing Site ◽  
Velocity Model ◽  
Low Velocity ◽  
Shallow Subsurface ◽  
Seismic Vibrations ◽  
First Time ◽  
Velocity Channel ◽  
Velocity Zone

AbstractOrbital and surface observations can shed light on the internal structure of Mars. NASA’s InSight mission allows mapping the shallow subsurface of Elysium Planitia using seismic data. In this work, we apply a classical seismological technique of inverting Rayleigh wave ellipticity curves extracted from ambient seismic vibrations to resolve, for the first time on Mars, the shallow subsurface to around 200 m depth. While our seismic velocity model is largely consistent with the expected layered subsurface consisting of a thin regolith layer above stacks of lava flows, we find a seismic low-velocity zone at about 30 to 75 m depth that we interpret as a sedimentary layer sandwiched somewhere within the underlying Hesperian and Amazonian aged basalt layers. A prominent amplitude peak observed in the seismic data at 2.4 Hz is interpreted as an Airy phase related to surface wave energy trapped in this local low-velocity channel.

Seismic tomography at a fire‐flood site

Geophysics ◽  
1989 ◽  
Vol 54 (9) ◽  
pp. 1082-1090 ◽  
Author(s):  
N. D. Bregman ◽  
P. A. Hurley ◽  
G. F. West
Keyword(s):  
Oil Recovery ◽  
Velocity Structure ◽  
Seismic Velocity ◽  
Pilot Project ◽  
Velocity Model ◽  
High Amplitude ◽  
Oil Sand ◽  
Low Velocity ◽  
Study Region ◽  
Velocity Channel

A crosshole seismic experiment was conducted to locate and characterize a firefront at an enhanced oil recovery (EOR) pilot project. The reservoir engineers involved in the project were interested in finding out why the burnfront apparently had stalled between two wells 51 m apart. In a noisy producing environment, good quality seismic data were recorded at depths ranging from 710 to 770 m. The frequency range of the data, 500 to 1500 Hz, allows resolution of the velocity structure on a scale of several meters. The moveout of first arrivals indicates that there are large velocity variations in the study region; a high‐amplitude, late arriving channel wave points to the existence of a low‐velocity channel connecting the boreholes. Using an iterative, nonlinear scheme which incorporates curved ray tracing and least‐squares inversion in each iteration, the first‐arrival times were inverted to obtain a two‐dimensional model of the compressional seismic velocity between the boreholes. The velocities range from 1.5 km/s to 3.2 km/s, with a low‐velocity channel at the depth of the producing oil sand. Sonic, core, and temperature logs lead us to conclude that the extremely low velocities in the model are probably due to gases produced by the burn. Increased velocities in an adjacent shale may be a secondary effect of the burn. The velocity model also indicates an irregularity in the topography at the bottom of the reservoir, an irregularity which may be responsible for blocking the progress of the burnfront.

scholarly journals Integrated magnetotelluric and seismic investigation of Cenozoic graben structure near Obrzycko, Poland

2021 ◽  
Author(s):  
Adam Cygal ◽  
Michał Stefaniuk ◽  
Anna Kret
Keyword(s):  
Seismic Data ◽  
Geophysical Methods ◽  
Geological Structure ◽  
Data Sets ◽  
Low Velocity ◽  
Shallow Subsurface ◽  
Geophysical Model ◽  
Novel Approach ◽  
Loose Deposits ◽  
Static Corrections

AbstractThis article presents the results of an integrated interpretation of measurements made using Audio-Magnetotellurics and Seismic Reflection geophysical methods. The obtained results were used to build an integrated geophysical model of shallow subsurface cover consisting of Cenozoic deposits, which then formed the basis for a detailed lithological and tectonic interpretation of deeper Mesozoic sediments. Such shallow covers, consisting mainly of glacial Pleistocene deposits, are typical for central and northern Poland. This investigation concentrated on delineating the accurate geometry of Obrzycko Cenozoic graben structure filled with loose deposits, as it was of great importance to the acquisition, processing and interpretation of seismic data that was to reveal the tectonic structure of the Cretaceous and Jurassic sediments which underly the study area. Previously, some problems with estimation of seismic static corrections over similar grabens filled with more recent, low-velocity deposits were encountered. Therefore, a novel approach to estimating the exact thickness of such shallow cover consisting of low-velocity deposits was applied in the presented investigation. The study shows that some alternative geophysical data sets (such as magnetotellurics) can be used to significantly improve the imaging of geological structure in areas where seismic data are very distorted or too noisy to be used alone

Super-Resolution of Seismic Velocity Model Guided by Seismic Data

2021 ◽  
pp. 1-12
Author(s):  
Yinshuo Li ◽  
Jianyong Song ◽  
Wenkai Lu ◽  
Patrice Monkam ◽  
Yile Ao
Keyword(s):  
Seismic Data ◽  
Seismic Velocity ◽  
Super Resolution ◽  
Velocity Model

SEISMIC VELOCITIES IN THE SOUTHEASTERN SAN JOAQUIN VALLEY OF CALIFORNIA

Geophysics ◽  
1941 ◽  
Vol 6 (4) ◽  
pp. 327-355
Author(s):  
E. J. Stulken
Keyword(s):  
Seismic Data ◽  
Seismic Velocity ◽  
San Joaquin Valley ◽  
Seismic Velocities ◽  
Velocity Measurements ◽  
Constant Depth ◽  
Entire Area ◽  
Velocity Gradients ◽  
Velocity Changes ◽  
First Time

For the first time, seismic velocity measurements from well surveys have been made intensively enough to justify an analysis of the velocity field in an entire area instead of just along lines between wells. Maps are drawn showing velocity changes in the southeastern San Joaquin Valley of California. A portion of the valley floor in the neighborhood of Bakersfield, about twenty‐five miles wide and thirty‐five miles long, was chosen for study because of the number of wells in the area whose velocities were known. Differences in average velocity of 1700 feet per second for a constant depth are observed, and horizontal velocity gradients averaging over 100 feet per second per mile are computed. Correction schemes for the adjustment of seismic data are suggested, and correction maps shown. An attempt is made to establish a connection between stratigraphy and seismic velocity. Comparative study of the logs of wells and the velocities observed in them yields certain qualitative conclusions, but attempts to express the relation in a quantitative way fail.

scholarly journals Improved imaging of gas hydrate reservoirs and their plumbing system using 2d elastic full waveform inversion

2021 ◽  
pp. 1-61
Author(s):  
Adnan Djeffal ◽  
Ingo A. Pecher ◽  
Satish C. Singh ◽  
Gareth J. Crutchley ◽  
Jari Kaipio
Keyword(s):  
Gas Hydrate ◽  
Waveform Inversion ◽  
Hydrate Formation ◽  
Velocity Model ◽  
Plumbing System ◽  
Low Velocity ◽  
Velocity Models ◽  
Full Waveform ◽  
Hydrate Reservoirs ◽  
Velocity Zone

Gas hydrates are ice-like crystalline materials that form under submarine environments of moderate pressure and low temperature. Another key factor to their formation is the abundance in gas supply from depth in addition to local biogenic gas. Detailed imaging and velocity analysis of the plumbing system of gas hydrates can provide confidence that amplitude anomalies in seismic data are related to gas hydrate accumulations. We have conducted 2D elastic full-waveform inversion (FWI) along a 14 km long segment of a 2D multichannel seismic profile to obtain a high-resolution velocity model of a hydrate system on the southern Hikurangi margin. We compare the FWI velocity model to previously published semblance- and tomography-based velocity models from the same data to explore how much more can be gained from the FWI. The FWI yielded a structurally more accurate velocity model that better delineated the low-velocity zone associated with free gas beneath the bottom simulating reflector (BSR) compared to the semblance- and tomography-based velocity models. Our results also find a lateral velocity inversion, that is, a narrow low-velocity zone surrounded by bands of higher velocities at a seaward-verging protothrust fault, which the two other methodologies failed to resolve. The FWI provides an improved lateral resolution making it an important tool when imaging the “plumbing” systems of gas hydrate reservoirs. In the southeastern limb of the anticline, our results find that the closely spaced landward-vergent protothrusts provide gas-charged fluids for hydrate formation above the BSR. Moreover, at the center of the anticline, our results find that a seaward-vergent protothrust fault appears to be acting as a conduit for gas-rich fluids into strata, although there is no accumulation of any significant hydrate above the BSR at the apex of the anticline. Our finding emphasizes the significance of densely spaced faults and fractures for providing gas for hydrate formation in the hydrate stability zone.

Seismic Velocity Model Building Using Neural Networks: Training Data Design and Learning Generalization

Geophysics ◽  
2021 ◽  
pp. 1-73
Author(s):  
Hani Alzahrani ◽  
Jeffrey Shragge
Keyword(s):  
Seismic Data ◽  
Model Building ◽  
Seismic Velocity ◽  
Velocity Model ◽  
Training Data ◽  
Training Process ◽  
Training Models ◽  
Velocity Models ◽  
Velocity Model Building ◽  
Layer Velocity

Data-driven artificial neural networks (ANNs) offer a number of advantages over conventional deterministic methods in a wide range of geophysical problems. For seismic velocity model building, judiciously trained ANNs offer the possibility of estimating high-resolution subsurface velocity models. However, a significant challenge of ANNs is training generalization, which is the ability of an ANN to apply the learning from the training process to test data not previously encountered. In the context of velocity model building, this means learning the relationship between velocity models and the corresponding seismic data from a set of training data, and then using acquired seismic data to accurately estimate unknown velocity models. We ask the following question: what type of velocity model structures need be included in the training process so that the trained ANN can invert seismic data from a different (hypothetical) geological setting? To address this question, we create four sets of training models: geologically inspired and purely geometrical, both with and without background velocity gradients. We find that using geologically inspired training data produce models with well-delineated layer interfaces and fewer intra-layer velocity variations. The absence of a certain geological structure in training models, though, hinders the ANN's ability to recover it in the testing data. We use purely geometric training models consisting of square blocks of varying size to demonstrate the ability of ANNs to recover reasonable approximations of flat, dipping, and curved interfaces. However, the predicted models suffer from intra-layer velocity variations and non-physical artifacts. Overall, the results successfully demonstrate the use of ANNs in recovering accurate velocity model estimates, and highlight the possibility of using such an approach for the generalized seismic velocity inversion problem.

An integrated 3D velocity inversion—joint hypocentral determination relocation analysis of events in the Northridge area

1996 ◽  
Vol 86 (1B) ◽  
pp. S138-S155
Author(s):  
Jose Pujol
Keyword(s):  
Weighted Average ◽  
Velocity Model ◽  
Actual Data ◽  
Low Velocity ◽  
Lateral Velocity ◽  
Epicentral Area ◽  
Velocity Inversion ◽  
Station Corrections ◽  
3D Velocity Model ◽  
Velocity Zone

Abstract A subset of 3371 events recorded in the Northridge area by the Southern California Seismic Network during January to April 1994 was relocated with the joint hypocentral determination (JHD) technique. This analysis showed two unexpected results: (a) the JHD locations are shifted about 3.9 km on average in a northwest direction with respect to the locations determined using a single-event location (SEL) program, and (b) the station corrections vary between −0.55 and 1.26 sec, a rather large range. In addition, the JHD locations are less scattered than the SEL locations. For each station, the weighted average of the arrival time residuals obtained when the events are located with the SEL program (which does not apply distance or error weighting) are generally smaller than the corresponding JHD corrections. The locations determined with SEL and using the weighted average residuals as station corrections do not differ much from the SEL locations, but on average the RMS residuals become as small as those corresponding to the JHD locations. As the magnitude of the station corrections indicates the presence of large lateral velocity variations, a 3D velocity model for the area was determined using the arrival times of 1012 events recorded by at least 17 stations. The initial velocity model was that used routinely by the Southern California Earthquake Center. The first two layers (5.5- and 10.5-km thick) were subdivided into 100 blocks each (12 × 12 km). These layers show a pronounced low-velocity anomaly (24% and 16%, respectively) immediately to the northwest of the epicentral area. This low-velocity zone coincides with the west Ventura Basin. Another pronounced low-velocity zone to the southeast of the epicentral area reflects the presence of the Los Angeles Basin. The locations obtained with the 3D velocity model are consistently to the southeast of the JHD locations, 2.4 km on average. To establish the effect of these pronounced lateral velocity variations on the SEL and JHD locations, synthetic travel times were analyzed. The synthetic times were generated for event locations determined by JHD (shifted by various amounts) and the 3D velocity model and were subsequently treated as the actual data. The most important result of this analysis is that the JHD locations are affected by a quasi-systematic shift in a northwest direction (up to about 2.7 km on average, depending on the initial shift) but that the relative locations are well preserved. Therefore, both the velocity inversion of the actual data and the analysis of the synthetic data indicate that the JHD locations determined for the actual data are quasi-systematically mislocated. To account for this mislocation, an overall shift of 2.5 km to the southeast was applied to all the JHD locations. One of the most important implications of the shifted locations is the possibility that the northeasterly dipping Santa Susana fault, to the northwest of the epicentral area, was seismically active during the aftershock sequence. This feature is more diffuse in other published locations.

scholarly journals Origin of the seismic belt in the San-in district, southwest Japan, inferred from the seismic velocity structure of the lower crust

2019 ◽  
Vol 71 (1) ◽  
Author(s):  
Hiroo Tsuda ◽  
Yoshihisa Iio ◽  
Takuo Shibutani
Keyword(s):  
Lower Crust ◽  
Velocity Structure ◽  
Seismic Velocity ◽  
Seismic Belt ◽  
Low Velocity ◽  
Intraplate Earthquakes ◽  
Linear Distribution ◽  
Low Velocity Zone ◽  
Velocity Anomaly ◽  
Velocity Zone

Abstract A long linear distribution of epicenters is seen along the Japan Sea coast in the San-in district located in southwestern Japan. This linear distribution of epicenters is called the seismic belt in the San-in district. The localization of intraplate earthquakes in the San-in district, far from plate boundaries, is not well understood. To answer this question, we look at the seismic velocity structure of the lower crust beneath the San-in district using seismic travel-time tomography. Our results show the existence of a low-velocity anomaly in the lower crust beneath the seismic belt. We infer that the deformation was concentrated in the low-velocity zone due to compressive stress caused by the subduction of oceanic plates, that stress concentration occurred just above the low-velocity zone, and that the seismic belt was therefore formed there. We also calculated the cutoff depths of shallow intraplate earthquakes in the San-in district. Based on the results, we consider the possible causes of the low-velocity anomaly in the lower crust beneath the seismic belt. We found that the cutoff depths of the intraplate earthquakes were shallower in the eastern part of the low-velocity zone in the lower crust beneath the seismic belt and deeper in the western part. Thus, the eastern part is likely to be hotter than the western part. We inferred that the eastern part was hot because a hot mantle upwelling approaches the Moho discontinuity below it and the resulting high temperature may be the main cause of the low-velocity anomaly. On the other hand, in the western part, we inferred that the temperature is not high because the mantle upwelling may not exist at shallow depth, and water dehydrated from the Philippine Sea plate reaches the lower crust, and the existence of this water may be the main cause of the low-velocity anomaly.

scholarly journals Deep-learning inversion: A next-generation seismic velocity model building method

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. R583-R599 ◽  
Author(s):  
Fangshu Yang ◽  
Jianwei Ma
Keyword(s):  
Deep Learning ◽  
Seismic Data ◽  
Model Building ◽  
Seismic Velocity ◽  
Velocity Model ◽  
Computational Time ◽  
Learning Methods ◽  
Velocity Models ◽  
Velocity Model Building ◽  
Training Stage

Seismic velocity is one of the most important parameters used in seismic exploration. Accurate velocity models are the key prerequisites for reverse time migration and other high-resolution seismic imaging techniques. Such velocity information has traditionally been derived by tomography or full-waveform inversion (FWI), which are time consuming and computationally expensive, and they rely heavily on human interaction and quality control. We have investigated a novel method based on the supervised deep fully convolutional neural network for velocity-model building directly from raw seismograms. Unlike the conventional inversion method based on physical models, supervised deep-learning methods are based on big-data training rather than prior-knowledge assumptions. During the training stage, the network establishes a nonlinear projection from the multishot seismic data to the corresponding velocity models. During the prediction stage, the trained network can be used to estimate the velocity models from the new input seismic data. One key characteristic of the deep-learning method is that it can automatically extract multilayer useful features without the need for human-curated activities and an initial velocity setup. The data-driven method usually requires more time during the training stage, and actual predictions take less time, with only seconds needed. Therefore, the computational time of geophysical inversions, including real-time inversions, can be dramatically reduced once a good generalized network is built. By using numerical experiments on synthetic models, the promising performance of our proposed method is shown in comparison with conventional FWI even when the input data are in more realistic scenarios. We have also evaluated deep-learning methods, the training data set, the lack of low frequencies, and the advantages and disadvantages of our method.

THE OFFSHORE CARPENTARIA BASIN-GULF OF CARPENTARIA, NORTH QUEENSLAND

1994 ◽  
Vol 34 (1) ◽  
pp. 614
Author(s):  
B.A. McConachie ◽  
P.W. Stainton ◽  
M.G. Barlow ◽  
J.N. Dunster
Keyword(s):  
Early Cretaceous ◽  
Seismic Data ◽  
Late Jurassic ◽  
Source Rocks ◽  
Low Velocity ◽  
Reservoir Rocks ◽  
Half Graben ◽  
Reservoir Sandstones ◽  
Cape York ◽  
Velocity Channel

The Carpentaria Basin is late Jurassic to early Cretaceous in age and underlies most of the Gulf of Carpentaria and surrounding onshore areas. The Carpentaria Basin is stratigraphically equivalent to the Eromanga and Papuan Basins where similar reservoir rocks produce large volumes of hydrocarbons.Drillholes Duyken–1, Jackie Ck–1 and 307RD12 provide regional lithostratigraphic and tectonic control for the Q22P permit in the offshore Carpentaria Basin. Duyken–1 penetrated the upper seal section in the Carpentaria Basin and a full sequence through the overlying Karumba Basin. Jackin Ck–1 intersected the lower reservoir units and a condensed upper seal section of the Carpentaria Basin. Coal drillhole 307RD12 tested the late Jurassic to early Cretaceous reservoir section in the Carpentaria Basin and also intersected an underlying Permian infrabasin sequence.Little is known of the pre Jurassic sedimentary section below the offshore Carpentaria Basin but at least two different rock packages appear to be present. The most encouraging are relatively small, layered, low velocity, channel and half-graben fill, possibly related to Permian or Permo-Triassic sedimentary rocks to the east in the Olive River area. The other packages consist of poorly defined, discontinuous, high velocity rocks believed to be related to those of the Bamaga Basin which have been mapped further north.During the period 1990-1993 Comalco Aluminium Limited reprocessed 2188 km of existing seismic data and acquired 2657 km of new seismic data over the offshore Carpentaria Basin. When combined with onshore seismic and the results of drilling previously undertaken by Comalco near Weipa on northwestern Cape York Peninsula, it was possible to define a significant and untested play in the Carpentaria Depression, the deepest part of the offshore Carpentaria Basin.The main play in the basin is the late Jurassic to early Cretaceous reservoir sandstones and source rocks, sealed by thick early Cretaceous mudstones. Possible pre-Jurassic source rocks are also present in discontinuous fault controlled half-grabens underlying the Carpentaria Basin. New detailed basin modelling suggests both the lower part of the Carpentaria Basin and any pre Jurassic section are mature within the depression and any source rocks present should have expelled oil.

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