scholarly journals Joint inversion of crosshole radar and seismic traveltimes acquired at the South Oyster Bacterial Transport Site

Geophysics ◽  
2008 ◽  
Vol 73 (4) ◽  
pp. G29-G37 ◽  
Author(s):  
Niklas Linde ◽  
Ari Tryggvason ◽  
John E. Peterson ◽  
Susan S. Hubbard
Keyword(s):  
Joint Inversion ◽  
Synthetic Data ◽  
Physical Property ◽  
Shallow Aquifer ◽  
Model Parameters ◽  
Structural Constraints ◽  
Integral Scale ◽  
Point Spread Functions ◽  
Traveltime Tomography ◽  
The Individual

The structural approach to joint inversion, entailing common boundaries or gradients, offers a flexible and effective way to invert diverse types of surface-based and/or crosshole geophysical data. The cross-gradients function has been introduced as a means to construct models in which spatial changes in two distinct physical-property models are parallel or antiparallel. Inversion methods that use such structural constraints also provide estimates of nonlinear and nonunique field-scale relationships between model parameters. Here, we jointly invert crosshole radar and seismic traveltimes for structurally similar models using an iterative nonlinear traveltime tomography algorithm. Application of the inversion scheme to synthetic data demonstrates that it better resolves lithologic boundaries than the individual inversions alone. Tests of the scheme on GPR and seismic data acquired within a shallow aquifer illustrate that the resultant models have improved correlations with flowmeter data in comparison with models based on individual inversions. The highest correlation with the flowmeter data is obtained when the joint inversion is combined with a stochastic regularization operator and the vertical integral scale is estimated from the flowmeter data. Point-spread functions show that the most significant resolution improvements offered by the joint inversion are in the horizontal direction.

scholarly journals Advanced Methods of Joint Inversion of Multiphysics Data for Mineral Exploration

Geosciences ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 262
Author(s):  
Michael S. Zhdanov ◽  
Michael Jorgensen ◽  
Leif Cox
Keyword(s):  
Joint Inversion ◽  
Mineral Exploration ◽  
A Priori ◽  
Geophysical Methods ◽  
Physical Property ◽  
Model Parameters ◽  
Time Inversion ◽  
Structural Constraints ◽  
Considerable Uncertainty ◽  
Additional Information

Different geophysical methods provide information about various physical properties of rock formations and mineralization. In many cases, this information is mutually complementary. At the same time, inversion of the data for a particular survey is subject to considerable uncertainty and ambiguity as to causative body geometry and intrinsic physical property contrast. One productive approach to reducing uncertainty is to jointly invert several types of data. Non-uniqueness can also be reduced by incorporating additional information derived from available geological and/or geophysical data in the survey area to reduce the searching space for the solution. This additional information can be incorporated in the form of a joint inversion of multiphysics data. This paper presents an overview of the main ideas and principles of novel methods of joint inversion, developed over the last decade, which do not require a priori knowledge about specific empirical or statistical relationships between the different model parameters and/or their attributes. These approaches are designated as follows: (1) Gramian constraints; (2) Gramian-based structural constraints; (3) localized Gramian constraints; and (4) joint focusing constraints. We provide a short description of the mathematical foundations of each of these approaches and discuss the practical aspects of their applications in mineral exploration.

Integration of diverse physical-property models: Subsurface zonation and petrophysical parameter estimation based on fuzzy c -means cluster analyses

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. H33-H44 ◽  
Author(s):  
Hendrik Paasche ◽  
Jens Tronicke ◽  
Klaus Holliger ◽  
Alan G. Green ◽  
Hansruedi Maurer
Keyword(s):  
Gamma Ray ◽  
Synthetic Data ◽  
Physical Property ◽  
Geophysical Data ◽  
Data Sets ◽  
Data Set ◽  
Petrophysical Parameters ◽  
Fcm Clustering ◽  
The Individual ◽  
Combine Information

Inversions of an individual geophysical data set can be highly nonunique, and it is generally difficult to determine petrophysical parameters from geophysical data. We show that both issues can be addressed by adopting a statistical multiparameter approach that requires the acquisition, processing, and separate inversion of two or more types of geophysical data. To combine information contained in the physical-property models that result from inverting the individual data sets and to estimate the spatial distribution of petrophysical parameters in regions where they are known at only a few locations, we demonstrate the potential of the fuzzy [Formula: see text]-means (FCM) clustering technique. After testing this new approach on synthetic data, we apply it to limited crosshole georadar, crosshole seismic, gamma-log, and slug-test data acquired within a shallow alluvial aquifer. The derived multiparameter model effectively outlines the major sedimentary units observed in numerous boreholes and provides plausible estimates for the spatial distributions of gamma-ray emitters and hydraulic conductivity.

Joint inversion of gravity and magnetic data for two-layer models

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. L35-L42 ◽  
Author(s):  
Mark Pilkington
Keyword(s):  
Least Squares ◽  
Joint Inversion ◽  
Physical Property ◽  
Magnetic Data ◽  
Model Parameters ◽  
Constant Density ◽  
Central Uplift ◽  
Gravity And Magnetic ◽  
Damped Least Squares ◽  
Gravity And Magnetic Data

Gravity and magnetic data are inverted jointly in terms of a model consisting of an interface separating two layers having a constant density and magnetization contrast. A damped least-squares inversion is used to determine the topography of the interface. The inversion requires knowledge of the physical property contrasts across the interface and its average depth. Since the relationship between model parameters and data is weakly nonlinear, a constant damped least-squares inverse is used during the iterative solution search. The effect of this inverse is closely related to a downward continuation of the field to the average interface depth. The method is used to map the base of the Sept-Iles mafic intrusion, Quebec, Canada, and the shape of the central uplift at the Chicxulub impact crater, Yucatan, Mexico. At Sept-Iles, the intrusion reaches a thickness of [Formula: see text], coincident with the maximum gravity anomaly, south of the intrusion center. At Chicxulub, the top of the central uplift is modeled to be [Formula: see text] deep and has a single peak form.

Reconstruction of 1-D conductivity from dual‐loop EM data

Geophysics ◽  
2000 ◽  
Vol 65 (2) ◽  
pp. 492-501 ◽  
Author(s):  
Zhiyi Zhang ◽  
Partha S. Routh ◽  
Douglas W. Oldenburg ◽  
David L. Alumbaugh ◽  
Gregory A. Newman
Keyword(s):  
Inverse Problem ◽  
Joint Inversion ◽  
Synthetic Data ◽  
Data Sets ◽  
Inversion Algorithm ◽  
Geological Structures ◽  
Electromagnetic Data ◽  
Independent Information ◽  
The Individual ◽  
Data Constraints

Inversions of electromagnetic data from different coil configurations provide independent information about geological structures. We develop a 1-D inversion algorithm that can invert data from the horizontal coplanar (HC), vertical coplanar, coaxial (CA), and perpendicular coil configurations separately or jointly. The inverse problem is solved by minimizing a model objective function subject to data constraints. Tests using synthetic data from 1-D models indicate that if data are collected at a sufficient number of frequencies, then the recovered models from individual inversions of different coil systems can be quite similar. However, if only a limited number of frequencies are available, then joint inversion of data from different coils produces a better model than the individual inversions. Tests on 3-D synthetic data sets indicate that 1-D inversions can be used as a fast and approximate tool to locate anomalies in the subsurface. Also for the test example presented here, the joint inversion of HC and CA data over a 3-D conductivity provided a better model than that produced by the individual inversion of the data sets.

scholarly journals ESTIMATION OF SEISMIC WAVES PARAMETERS WITH APPLICATION OF A GENETIC ALGORITHM

2018 ◽  
pp. 51-58
Author(s):  
R. R. Sultangaleev ◽  
V. N. Troyan
Keyword(s):  
Genetic Algorithm ◽  
Seismic Waves ◽  
Fitness Function ◽  
Random Number Generator ◽  
Synthetic Data ◽  
Threshold Value ◽  
Velocity Estimation ◽  
Model Parameters ◽  
Basic Step ◽  
The Individual

A Genetic algorithm (GA) is a very important method for the solution of non-linear problems. The basic steps in GA are coding, selection, crossover, mutation and choice. Coding is a way of representing data  in binary notation. The algorithm must determine the fitness of the individual models. This means that  the binary information is decoded into the physical model parameters and the forward problem is solved. The resulting synthetic data is estimated, then compared with the actual observed data using the  specific fitness criteria. The selection of pairs of the individual models for the reproduction is based on  their fitness values. Models with the higher fitness values are more likely to get the selection than models with low  fitness values. A crossover caused the exchange of some information between the paired models thereby  generating new models. The mutation is a random change of binary state. The condition of the procedure of mutation: if a value obtained by a random number generator is less than a certain threshold value, the  mutation procedure is performed. The last basic step in GA is choice. We choose from each pairs a model,  which has the less fitness function. Then we produce the procedures: the crossover, the mutation and the  choice. This procedure is continued until we obtain the optimal model. We have used the GA for the  estimation of the velocity for the gradient layer. The synthetic seismogram was calculated by the finite- difference method. The obtained results showed a high effectiveness of GA for the seismic waves velocity estimation.

Improvement in MRS parameter estimation by joint and laterally constrained inversion of MRS and TEM data

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. WB191-WB200 ◽  
Author(s):  
Ahmad A. Behroozmand ◽  
Esben Auken ◽  
Gianluca Fiandaca ◽  
Anders Vest Christiansen
Keyword(s):  
Water Content ◽  
Joint Inversion ◽  
Synthetic Data ◽  
Clear Correlation ◽  
Model Parameters ◽  
Dc Resistivity ◽  
Borehole Data ◽  
Simultaneous Inversion ◽  
Transient Electromagnetic ◽  
Magnetic Resonance Sounding

We developed a new scheme for joint and laterally constrained inversion (LCI) of magnetic resonance sounding (MRS) data and transient electromagnetic (TEM) data, which greatly improves the estimation of the MRS model parameters. During the last few decades, electrical and electromagnetic methods have been widely used for groundwater investigation, but they suffer from some inherent limitations; for example, equivalent layer sequences. Furthermore, the water content information is only empirically correlated to resistivity of the formation. MRS is a noninvasive geophysical technique that directly quantifies the water content distribution from surface measurements. The resistivity information of the subsurface is obtained from a complementary geophysical method such as TEM or DC resistivity methods. The conventional inversion of MRS data assumes the resulting resistivity structure to be correct and considers a constant MRS kernel through the inversion. We found that this assumption may introduce an error to the forward modeling and consequently could result in erroneous parameter estimations in the inversion process. We investigated the advantage of TEM for the joint inversion compared to DC resistivity. A fast and numerically efficient MRS forward routine made it possible to invert the MRS and TEM data sets simultaneously along profiles. Furthermore, by application of lateral constraints on the model parameters, lateral smooth 2D model sections could be be obtained. The simultaneous inversion for resistivity and MRS parameters led to a more reliable and robust estimation of all parameters, and the MRS data diminished the range of equivalent resistivity models. We examined the approach through synthetic data and a field example in Denmark where good agreement with borehole data was demonstrated with clear correlation between the relaxation time [Formula: see text] and the grain size distribution of a sandy aquifer.

A study of fuzzy c-means coupling for joint inversion, using seismic tomography and gravity data test scenarios

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. W1-W15 ◽  
Author(s):  
Angela Carter-McAuslan ◽  
Peter G. Lelièvre ◽  
Colin G. Farquharson
Keyword(s):  
Seismic Velocity ◽  
Joint Inversion ◽  
Gravity Data ◽  
A Priori ◽  
Synthetic Data ◽  
Physical Property ◽  
Massive Sulfide ◽  
Realistic Model ◽  
Fuzzy C Means ◽  
Coupling Approach

Joint inversion, the inversion of multiple geophysical data sets containing complementary information about the subsurface, has the potential to significantly improve inversion results by reducing the nonuniqueness of the inverse problem. One of the challenges of joint inversion is deciding how to couple the multiple physical property models. If a coupling approach is used that is inconsistent with the physical truth, then inversion artifacts can occur and may lead to incorrect interpretations. In this paper, we investigated the fuzzy c-means (FCM) clustering approach to provide a lithological coupling of the seismic velocity and density models in joint 2D inversions of first-arrival traveltimes and gravity data. Even though this coupling approach has been used in previous works, recommendations for its effective use have not yet been developed. We conducted a suite of joint inversion tests on synthetic data generated from a geologically realistic model based on magmatic massive sulfide deposits. There is a known relationship between seismic velocity and density for the silicate rocks and sulfide minerals involved; this lithological relationship was used to design a clustered coupling strategy in the joint inversions. The tests we conducted clearly exhibited the benefits of joint inversion using FCM coupling. Our work revealed the effects of including inaccurate a priori physical property information. We also evaluated approaches to assess whether such inaccurate information may have been used.

scholarly journals A Multiple Stakeholder Perspective for Evaluating Community-Based Dementia Care

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 60-61
Author(s):  
Johan Suen
Keyword(s):  
Dementia Care ◽  
Structural Constraints ◽  
Care Provision ◽  
Care Providers ◽  
Structured Interviews ◽  
Community Based ◽  
Relational Factors ◽  
Care Relationships ◽  
The Individual ◽  
The Impact

Abstract For holistic interventions and research on dementia, it is fundamental to understand care experiences from the perspectives of carers, care recipients, and care professionals. While research on care dyads and triads have highlighted the effects of communication and interactional aspects on care relationships, there is a lack of knowledge on how individual-contextual and relational factors shape the provision and receipt of care in terms of decision-making processes, resource allocation, and expectations of care outcomes. Thus, this paper sheds light on (i) how carers negotiate care provision with other important life domains such as employment, household/family roles and conflicts, as well as their own health problems, life goals, values, and aspirations for ageing; (ii) how older adults with dementia perceive support and those who provide it; (iii) the structural constraints faced by care professionals in delivering a team-based mode of dementia care; and, taken together, (iv) how community-based dementia care is impeded by barriers at the individual, relational, and institutional levels. Findings were derived from semi-structured interviews and observational data from fieldwork conducted with 20 persons with dementia (median age = 82), 20 of their carers (median age = 60), and 4 professional care providers. All respondents were clients and staff of a multidisciplinary and community-based dementia care system in Singapore. Our analysis indicates the impact of dementia care is strongly mediated by the interplay between institutional/familial contexts of care provision and the various ‘orientations’ to cognitive impairment and seeking support, which we characterised as ‘denial/acceptance’, ‘obligated’, ‘overprotective’, and ‘precariously vulnerable’.

scholarly journals A flexible framework for sequential estimation of model parameters in computational hemodynamics

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Christopher J. Arthurs ◽  
Nan Xiao ◽  
Philippe Moireau ◽  
Tobias Schaeffter ◽  
C. Alberto Figueroa
Keyword(s):  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Sequential Estimation ◽  
Wall Material ◽  
Patient Specific ◽  
Model Parameters ◽  
Computational Framework ◽  
Lumped Parameter ◽  
Estimation Of Model Parameters

AbstractA major challenge in constructing three dimensional patient specific hemodynamic models is the calibration of model parameters to match patient data on flow, pressure, wall motion, etc. acquired in the clinic. Current workflows are manual and time-consuming. This work presents a flexible computational framework for model parameter estimation in cardiovascular flows that relies on the following fundamental contributions. (i) A Reduced-Order Unscented Kalman Filter (ROUKF) model for data assimilation for wall material and simple lumped parameter network (LPN) boundary condition model parameters. (ii) A constrained least squares augmentation (ROUKF-CLS) for more complex LPNs. (iii) A “Netlist” implementation, supporting easy filtering of parameters in such complex LPNs. The ROUKF algorithm is demonstrated using non-invasive patient-specific data on anatomy, flow and pressure from a healthy volunteer. The ROUKF-CLS algorithm is demonstrated using synthetic data on a coronary LPN. The methods described in this paper have been implemented as part of the CRIMSON hemodynamics software package.

Joint Inversion of Electromagnetic and Seismic Data Based on Structural Constraints Using Variational Born Iteration Method

2018 ◽  
Vol 56 (1) ◽  
pp. 436-445 ◽  
Author(s):  
Tian Lan ◽  
Hai Liu ◽  
Na Liu ◽  
Jinghe Li ◽  
Feng Han ◽  
...  
Keyword(s):  
Seismic Data ◽  
Iteration Method ◽  
Joint Inversion ◽  
Structural Constraints
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