OCSA inversion: A joint inversion method with Occam's inversion and SA inversion for MT

2017 ◽  
Author(s):  
Xin Hui* ◽  
Xiaoping Wu
Keyword(s):  
Joint Inversion ◽  
Inversion Method ◽  
Occam’S Inversion

scholarly journals Imaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion

2020 ◽  
Vol 222 (3) ◽  
pp. 1639-1655
Author(s):  
Xin Zhang ◽  
Corinna Roy ◽  
Andrew Curtis ◽  
Andy Nowacki ◽  
Brian Baptie
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Joint Inversion ◽  
Body Wave ◽  
Source Parameters ◽  
Wave Dispersion ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Wave Data

SUMMARY Seismic body wave traveltime tomography and surface wave dispersion tomography have been used widely to characterize earthquakes and to study the subsurface structure of the Earth. Since these types of problem are often significantly non-linear and have non-unique solutions, Markov chain Monte Carlo methods have been used to find probabilistic solutions. Body and surface wave data are usually inverted separately to produce independent velocity models. However, body wave tomography is generally sensitive to structure around the subvolume in which earthquakes occur and produces limited resolution in the shallower Earth, whereas surface wave tomography is often sensitive to shallower structure. To better estimate subsurface properties, we therefore jointly invert for the seismic velocity structure and earthquake locations using body and surface wave data simultaneously. We apply the new joint inversion method to a mining site in the United Kingdom at which induced seismicity occurred and was recorded on a small local network of stations, and where ambient noise recordings are available from the same stations. The ambient noise is processed to obtain inter-receiver surface wave dispersion measurements which are inverted jointly with body wave arrival times from local earthquakes. The results show that by using both types of data, the earthquake source parameters and the velocity structure can be better constrained than in independent inversions. To further understand and interpret the results, we conduct synthetic tests to compare the results from body wave inversion and joint inversion. The results show that trade-offs between source parameters and velocities appear to bias results if only body wave data are used, but this issue is largely resolved by using the joint inversion method. Thus the use of ambient seismic noise and our fully non-linear inversion provides a valuable, improved method to image the subsurface velocity and seismicity.

Inversion of Reservoir Parameters by Ultra-High Temperature and High Pressure CO2 Gas Reservoirs with Nuclear Logging

2021 ◽  
Author(s):  
Hengrong Zhang ◽  
Lizhi Xiao ◽  
Wensheng Wu ◽  
Xinyue Fu ◽  
Shenglin He
Keyword(s):  
Joint Inversion ◽  
Simulation Method ◽  
Inversion Method ◽  
Burial Depth ◽  
Gas Reservoirs ◽  
Co2 Gas ◽  
Carbonate Cement ◽  
Response Equation ◽  
Temperature And Pressure ◽  
The Difference

Abstract The Yinggehai basin is located in the western part of the South China Sea, the burial depth of the Huangliu and Meishan formations in the target layer is close to 4000 meters, the formation temperature is close to 200 degrees Celsius, and the formation pressure is up to 100 MPa. The reservoir is characterized by low porosity-ultra-low permeability, heavy carbonate cement, complex CO2 content, this leads to complex neutron and density logging effects. The solubility of CO2 Above CH4, the solubility change with temperature and pressure is different from CH4, which makes it difficult to identify the CO2 gas layer. In this paper, based on the difference in the physical characteristics of CO2 and CH4, the Boltzmann equation combined with MCNP software was used to simulate the neutron and density logging responses under different CO2 saturations. Environmental factors such as temperature and pressure, carbonate cement, mud content and pores were studied To measure the effect of logging response, the LM inversion method is used to jointly invert CO2 saturation of density and neutron logs. The purpose of the inversion is to reduce the non-uniqueness of the evaluation of porosity and CO2 saturation. By introducing the Levenberg-Marquardt (LM) method, the neutron logging response equation of the porosity, argillaceous content, CO2, CH4 in the rock and the corresponding temperature and pressure is solved, and also the response equation of above parameters to density logging, where porosity and CO2 content are the key parameters, and the calculation results prove the effectiveness of the method by comparing the sampling data. The results show that the accuracy of the estimated CO2 saturation is increased by 10% compared with the conventional interpretation method, and the new simulation method improves the calculation speed several times compared to the MCNP software. The joint inversion method has been successfully applied to field data, which has greatly improved the saturation evaluation results of traditional logging interpretation methods, can be extended to other fields of nuclear logging simulation and inversion.

A new crustal shear-velocity model in Southwest China from joint seismological inversion and its implications for regional crustal dynamics

2019 ◽  
Author(s):  
Yan Yang ◽  
Huajian Yao ◽  
Hanxiao Wu ◽  
Ping Zhang ◽  
Maomao Wang
Keyword(s):  
Tibetan Plateau ◽  
Rayleigh Wave ◽  
Joint Inversion ◽  
Shear Velocity ◽  
P Wave ◽  
Tectonic Deformation ◽  
Inversion Method ◽  
Low Velocity ◽  
Sw China ◽  
S Period

SUMMARY Southwest (SW) China is located in a transition site from the active Tibetan Plateau to the stable Yangtze craton, which has complicated tectonic deformation and severe seismic hazards. We combine data from ambient noise, teleseismic body and surface waves, and petroleum wells to better constrain the crustal shear-velocity structure in SW China. We jointly invert the Rayleigh wave dispersion (5–40 s period), Rayleigh wave ZH ratio (20–60 s period), and P-wave receiver function for 114 permanent stations with a stepwise linearized joint inversion method. Compared to previous tomography results, we observe higher shear velocity in the sedimentary rocks within the Sichuan Basin, which is consistent with sonic logging measurements. Our model reveals widespread low-velocity zones in the mid-lower crust, and their boundaries correlate well with major fault systems. Between two main mid-crustal low-velocity channels, a prominent high-velocity region surrounded by earthquakes is observed in the inner zone of the Emeishan large igneous province (ELIP) and around the Anninghe-Zemuhe fault zone. These observations are comparable to regional tomography results using very dense arrays. Based on the results, we suggest that mid-lower crustal ductile flow and upper-crustal rigid fault movement play equally important roles in controlling the regional deformation styles and earthquake distribution in SW China. Our results also resolve thick crust-mantle transition zones beneath the eastern Tibetan Plateau and the inner zone of the ELIP due to ‘top-down’ and ‘bottom-up’ crust-mantle interactions, respectively. Our new model can serve as a reference crustal model of future high resolution model construction in SW China.

Joint inversion of two-dimensional magnetotelluric and surface wave dispersion data with cross-gradient constraints

2020 ◽  
Vol 221 (2) ◽  
pp. 938-950
Author(s):  
Pingping Wu ◽  
Handong Tan ◽  
Changhong Lin ◽  
Miao Peng ◽  
Huan Ma ◽  
...  
Keyword(s):  
Surface Wave ◽  
Velocity Structure ◽  
Joint Inversion ◽  
Wave Dispersion ◽  
Uniqueness Problem ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Surface Wave Dispersion ◽  
Gradient Constraints ◽  
Dispersion Data

SUMMARY Multiphysics imaging for data inversion is of growing importance in many branches of science and engineering. Cross-gradient constraint has been considered as a feasible way to reduce the non-uniqueness problem inherent in inversion process by finding geometrically consistent images from multigeophysical data. Based on OCCAM inversion algorithm, a direct inversion method of 2-D profile velocity structure with surface wave dispersion data is proposed. Then we jointly invert the profiles of magnetotelluric and surface wave dispersion data with cross-gradient constraints. Three synthetic models, including block homogeneous or heterogeneous models with consistent or inconsistent discontinuities in velocity and resistivity, are presented to gauge the performance of the joint inversion scheme. We find that owning to the complementary advantages of the two geophysical data sets, the models recovered with structure coupling constraints exhibit higher resolution in the classification of complex geologic units and settle some imaging problems caused by the separate inversion methods. Finally, a realistic velocity model from the NE Tibetan Plateau and its corresponding resistivity model calculated by empirical law are used to test the effectiveness of the joint inversion scheme in the real geological environment.

Quantitative CO2 monitoring at the CaMI Field Research Station (CaMI.FRS), Canada, using a hybrid structural-petrophysical joint inversion

2020 ◽  
Author(s):  
Dennis Rippe ◽  
Michael Jordan ◽  
Marie Macquet ◽  
Don Lawton ◽  
Anouar Romdhane ◽  
...  
Keyword(s):  
Joint Inversion ◽  
Field Research ◽  
Research Centre ◽  
Inversion Method ◽  
Model Parameters ◽  
Research Station ◽  
Geophysical Monitoring ◽  
Monitoring Techniques ◽  
Research Institutes ◽  
Structural Joint

<p>A key requirement by the European CCS directive for the safe operation of geological CO<sub>2</sub> storage is the operator's responsibility to demonstrate containment of the injected CO<sub>2</sub> and conformance between its actual and modelled behavior. Understanding the subsurface behavior and long-term fate of the injected CO<sub>2</sub> requires the quantification of key reservoir parameters (e.g. pore pressure, CO<sub>2</sub> saturation and strain in the overburden). Reliable quantification of these parameters and distinction between them pose a challenge for conventional monitoring techniques, which could be overcome by combining advanced multi-disciplinary and multi-method monitoring techniques in a joint inversion.</p><p>Within the <strong>aCQurate</strong> project, we aim to develop a new technology for <strong>a</strong>ccurate <strong>CO<sub>2</sub></strong> monitoring using <strong>Qu</strong>antitative joint inversion for la<strong>r</strong>ge-sc<strong>a</strong>le on-shore and off-shore s<strong>t</strong>orag<strong>e</strong> applications. In previous applications of joint inversion to CO<sub>2</sub> monitoring, we successfully combined the strengths and advantages of different geophysical monitoring techniques (i.e. seismics with its high spatial resolution and geoelectrics with its high sensitivity to changes in CO<sub>2</sub> saturation), using a cross-gradient approach to achieve structural similarity between the different models. While this structural joint inversion provides a robust link between models of different geophysical monitoring techniques, it lacks a quantitative calibration of the model parameters based on valid rock-physics models. This limitation is addressed by extending the previously developed structural joint inversion method into a hybrid structural-petrophysical joint inversion, which allows integration of cross-property relations, e.g. derived from well logs.</p><p>The hybrid structural-petrophysical joint inversion integrates relevant geophysical monitoring techniques in a modular way, including seismic, electric and potential field methods (FWI, CSEM, ERT, MMR and gravity). It is implemented using a Bayes formulation, which allows proper weighting of the different models and data sets, as well as the relevant structural and petrophysical joint inversion constraints during the joint inversion.</p><p>The hybrid joint inversion is designed for on-shore and off-shore CO<sub>2</sub> storage applications and will be demonstrated using synthetic data from the CaMI Field Research Station (CaMI.FRS) in Canada. CaMI.FRS is operated by the Containment and Monitoring Institute (CaMI) of CMC Research Institutes, Inc., and provides an ideal platform for the development and deployment of advanced CO<sub>2</sub> monitoring technologies. CO<sub>2</sub> injection occurs at 300 m depth into the Basal Belly River sandstone formation, which is monitored using a large variety of geophysical and geochemical monitoring techniques. In preparation for the application to real monitoring data, we present the application of the joint inversion to synthetic full waveform inversion (FWI) and electrical resistivity tomography (ERT) data, derived for a geostatic model with dynamic fluid flow simulations.</p><p>In addition to obtaining a better understanding of the subsurface behavior of the injected CO<sub>2</sub> at CaMI.FRS, our goal is to mature the joint inversion technology further towards large-scale CO<sub>2</sub> storage applications, e.g. on the Norwegian Continental Shelf.</p><p><strong>Acknowledgements</strong></p><p>Funding is provided by the Norwegian CLIMIT program (project number 616067), Equinor ASA, CMC Research Institutes, Inc., University of Calgary, Lawrence Berkeley National Laboratory (LBNL), Institut national de la recherche scientifique (INRS), Quad Geometrics Norway AS and GFZ German Research Centre For Geosciences (GFZ).</p>

An efficient data‐subspace inversion method for 2-D magnetotelluric data

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 791-803 ◽  
Author(s):  
Weerachai Siripunvaraporn ◽  
Gary Egbert
Keyword(s):  
Significant Loss ◽  
Inversion Method ◽  
Data Sets ◽  
Reduced Basis ◽  
Sensitivity Matrix ◽  
Approximate Methods ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Data Space ◽  
Occam’S Inversion

There are currently three types of algorithms in use for regularized 2-D inversion of magnetotelluric (MT) data. All seek to minimize some functional which penalizes data misfit and model structure. With the most straight‐forward approach (exemplified by OCCAM), the minimization is accomplished using some variant on a linearized Gauss‐Newton approach. A second approach is to use a descent method [e.g., nonlinear conjugate gradients (NLCG)] to avoid the expense of constructing large matrices (e.g., the sensitivity matrix). Finally, approximate methods [e.g., rapid relaxation inversion (RRI)] have been developed which use cheaply computed approximations to the sensitivity matrix to search for a minimum of the penalty functional. Approximate approaches can be very fast, but in practice often fail to converge without significant expert user intervention. On the other hand, the more straightforward methods can be prohibitively expensive to use for even moderate‐size data sets. Here, we present a new and much more efficient variant on the OCCAM scheme. By expressing the solution as a linear combination of rows of the sensitivity matrix smoothed by the model covariance (the “representers”), we transform the linearized inverse problem from the M-dimensional model space to the N-dimensional data space. This method is referred to as DASOCC, the data space OCCAM’s inversion. Since generally N ≪ M, this transformation by itself can result in significant computational saving. More importantly the data space formulation suggests a simple approximate method for constructing the inverse solution. Since MT data are smooth and “redundant,” a subset of the representers is typically sufficient to form the model without significant loss of detail. Computations required for constructing sensitivities and the size of matrices to be inverted can be significantly reduced by this approximation. We refer to this inversion as REBOCC, the reduced basis OCCAM’s inversion. Numerical experiments on synthetic and real data sets with REBOCC, DASOCC, NLCG, RRI, and OCCAM show that REBOCC is faster than both DASOCC and NLCG, which are comparable in speed. All of these methods are significantly faster than OCCAM, but are not competitive with RRI. However, even with a simple synthetic data set, we could not always get RRI to converge to a reasonable solution. The basic idea behind REBOCC should be more broadly applicable, in particular to 3-D MT inversion.

scholarly journals Asteroid models reconstructed from the Lowell Photometric Database and WISE data

2018 ◽  
Vol 617 ◽  
pp. A57 ◽  
Author(s):  
J. Ďurech ◽  
J. Hanuš ◽  
V. Alí-Lagoa
Keyword(s):  
Joint Inversion ◽  
Rotation Period ◽  
Thermal Infrared ◽  
Light Curves ◽  
Physical Models ◽  
Infrared Light ◽  
Inversion Method ◽  
Significant Discrepancy ◽  
Wide Range ◽  
New Models

Context. Information about the spin state of asteroids is important for our understanding of the dynamical processes affecting them. However, spin properties of asteroids are known for only a small fraction of the whole population. Aims. To enlarge the sample of asteroids with a known rotation state and basic shape properties, we combined sparse-in-time photometry from the Lowell Observatory Database with flux measurements from NASA’s WISE satellite. Methods. We applied the light curve inversion method to the combined data. The thermal infrared data from WISE were treated as reflected light because the shapes of thermal and visual light curves are similar enough for our purposes. While sparse data cover a wide range of geometries over many years, WISE data typically cover an interval of tens of hours, which is comparable to the typical rotation period of asteroids. The search for best-fitting models was done in the framework of the Asteroids@home distributed computing project. Results. By processing the data for almost 75 000 asteroids, we derived unique shape models for about 900 of them. Some of them were already available in the DAMIT database and served us as a consistency check of our approach. In total, we derived new models for 662 asteroids, which significantly increased the total number of asteroids for which their rotation state and shape are known. For another 789 asteroids, we were able to determine their sidereal rotation period and estimate the ecliptic latitude of the spin axis direction. We studied the distribution of spins in the asteroid population. Apart from updating the statistics for the dependence of the distribution on asteroid size, we revealed a significant discrepancy between the number of prograde and retrograde rotators for asteroids smaller than about 10 km. Conclusions. Combining optical photometry with thermal infrared light curves is an efficient approach to obtaining new physical models of asteroids. The amount of asteroid photometry is continuously growing and joint inversion of data from different surveys could lead to thousands of new models in the near future.

scholarly journals Joint inversion of strain and tilt data using the Akaike’s Bayesian information criterion to map detailed slip distributions of short-term slow slip events

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Takahiro Tsuyuki ◽  
Akio Kobayashi ◽  
Reiko Kai ◽  
Takeshi Kimura ◽  
Satoshi Itaba
Keyword(s):  
Bayesian Information Criterion ◽  
Joint Inversion ◽  
Information Criterion ◽  
Inversion Method ◽  
Slow Slip ◽  
Short Term ◽  
Plate Interface ◽  
Slow Slip Events ◽  
Probability Estimates ◽  
Method Yield

AbstractAlong the Nankai Trough subduction zone, southwest Japan, short-term slow slip events (SSEs) are commonly detected in strain and tilt records. These observational data have been used in rectangular fault models with uniform slip to analyze SSEs; however, the assumption of uniform slip precludes the possibility of mapping the slip distribution in detail. We report here an inversion method, based on the joint use of strain and tilt data and evaluated in terms of the Akaike’s Bayesian information criterion (ABIC), to estimate the slip distributions of short-term SSEs on the plate interface. Tests of this method yield slip distributions with smaller errors than are possible with the use of strain or tilt data alone. This method provides detailed spatial slip distributions of short-term SSEs including probability estimates, enabling improved monitoring of their locations and amounts of slip.

scholarly journals Adaptive moment-tensor joint inversion of clustered microseismic events for monitoring geological carbon storage

2019 ◽  
Vol 219 (1) ◽  
pp. 80-93
Author(s):  
Yu Chen ◽  
Lianjie Huang
Keyword(s):  
Carbon Storage ◽  
Oil Recovery ◽  
Joint Inversion ◽  
Moment Tensor ◽  
Crack Opening ◽  
Cost Effective ◽  
Microseismic Monitoring ◽  
Moment Tensor Inversion ◽  
Inversion Method ◽  
Microseismic Events

SUMMARY Moment-tensor inversion of induced microseismic events can provide valuable information for tracking CO2 plumes at geological carbon storage sites, and study the physical mechanism of induced microseismicity. Accurate moment-tensor inversion requires a wide-azimuthal coverage of geophones. Cost-effective microseismic monitoring for geological carbon storage often uses only one geophone array within a borehole, leading to a large uncertainty in moment-tensor inversion. We develop a new adaptive moment-tensor joint inversion method to reduce the inversion uncertainty, when using limited but typical geophone receiver geometries. We first jointly invert a number of clustered microseismic events using a uniform focal mechanism to minimize the waveform misfit between observed and predicted P and S waveforms. We then invert the moment tensor for each event within a limited searching range around the joint inversion result. We apply our adaptive joint inversion method to microseismic data acquired using a single borehole geophone array at the CO2-Enhanced Oil Recovery field at Aneth, Utah. We demonstrate that our inversion method is capable of reducing the inversion uncertainty caused by the limited azimuthal coverage of geophones. Our inverted strikes of focal mechanisms of microseismic events are consistent with the event spatial distribution in subparallel pre-existing fractures or geological imperfections. The large values up to 40 per cent of the CLVD components might indicate crack opening induced by CO2/wastewater injection or rupture complexity.

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