Relevant bibliographies by topics / Inversion modelling

Academic literature on the topic 'Inversion modelling'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Inversion modelling"

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Zwaan, Frank, Guido Schreurs, Susanne J. H. Buiter, Oriol Ferrer, Riccardo Reitano, Michael Rudolf, and Ernst Willingshofer. "Analogue modelling of basin inversion: a review and future perspectives." Solid Earth 13, no. 12 (December 16, 2022): 1859–905. http://dx.doi.org/10.5194/se-13-1859-2022.

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Abstract. Basin inversion involves the reversal of subsidence in a basin due to compressional tectonic forces, leading to uplift of the basin's sedimentary infill. Detailed knowledge of basin inversion is of great importance for scientific, societal, and economic reasons, spurring continued research efforts to better understand the processes involved. Analogue tectonic modelling forms a key part of these efforts, and analogue modellers have conducted numerous studies of basin inversion. In this review paper we recap the advances in our knowledge of basin inversion processes acquired through analogue modelling studies, providing an up-to-date summary of the state of analogue modelling of basin inversion. We describe the different definitions of basin inversion that are being applied by researchers, why basin inversion has been historically an important research topic and what the general mechanics involved in basin inversion are. We subsequently treat the wide range of different experimental approaches used for basin inversion modelling, with attention to the various materials, set-ups, and techniques used for model monitoring and analysing the model results. Our new systematic overviews of generalized model results reveal the diversity of these results, which depend greatly on the chosen set-up, model layering and (oblique) kinematics of inversion, and 3D along-strike structural and kinematic variations in the system. We show how analogue modelling results are in good agreement with numerical models, and how these results help researchers to better understand natural examples of basin inversion. In addition to reviewing the past efforts in the field of analogue modelling, we also shed light on future modelling challenges and identify a number of opportunities for follow-up research. These include the testing of force boundary conditions, adding geological processes such as sedimentation, transport, and erosion; applying state-of-the-art modelling and quantification techniques; and establishing best modelling practices. We also suggest expanding the scope of basin inversion modelling beyond the traditional upper crustal “North Sea style” of inversion, which may contribute to the ongoing search for clean energy resources. It follows that basin inversion modelling can bring valuable new insights, providing a great incentive to continue our efforts in this field. We therefore hope that this review paper will form an inspiration for future analogue modelling studies of basin inversion.
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Chevallier, F. "On the parallelization of atmospheric inversions of CO<sub>2</sub> surface fluxes within a variational framework." Geoscientific Model Development 6, no. 3 (June 7, 2013): 783–90. http://dx.doi.org/10.5194/gmd-6-783-2013.

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Abstract. The variational formulation of Bayes' theorem allows inferring CO2 sources and sinks from atmospheric concentrations at much higher time–space resolution than the ensemble or analytical approaches. However, it usually exhibits limited scalable parallelism. This limitation hinders global atmospheric inversions operated on decadal time scales and regional ones with kilometric spatial scales because of the computational cost of the underlying transport model that has to be run at each iteration of the variational minimization. Here, we introduce a physical parallelization (PP) of variational atmospheric inversions. In the PP, the inversion still manages a single physically and statistically consistent window, but the transport model is run in parallel overlapping sub-segments in order to massively reduce the computation wall-clock time of the inversion. For global inversions, a simplification of transport modelling is described to connect the output of all segments. We demonstrate the performance of the approach on a global inversion for CO2 with a 32 yr inversion window (1979–2010) with atmospheric measurements from 81 sites of the NOAA global cooperative air sampling network. In this case, we show that the duration of the inversion is reduced by a seven-fold factor (from months to days), while still processing the three decades consistently and with improved numerical stability.
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Chevallier, F. "On the parallelization of atmospheric inversions of CO<sub>2</sub> surface fluxes within a variational framework." Geoscientific Model Development Discussions 6, no. 1 (January 8, 2013): 37–57. http://dx.doi.org/10.5194/gmdd-6-37-2013.

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Abstract. The variational formulation of Bayes' theorem allows inferring CO2 sources and sinks from atmospheric concentrations at much higher space-time resolution than the ensemble approach or the analytical one. However, it usually exhibits limited scalable parallelism. This limitation hinders global atmospheric inversions operated on decadal time scales and regional ones with kilometric spatial scales, because of the computational cost of the underlying transport model that has to be run at each iteration of the variational minimization. Here, we introduce a Physical Parallelisation (PP) of variational atmospheric inversions. In the PP, the inversion still manages a single physically and statistically consistent window, but the transport model is run in parallel overlapping sub-segments in order to massively reduce the computation wall clock time of the inversion. For global inversions, a simplification of transport modelling is described to connect the output of all segments. We demonstrate the performance of the approach on a global inversion for CO2 with a 32-yr inversion window (1979–2010) with atmospheric measurements from 81 sites of the NOAA global cooperative air sampling network. In this case, we show that the duration of the inversion is reduced by a seven-fold factor (from months to days) while still processing the three decades consistently and with improved numerical stability.
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Ellis, Robert G. "Airborne Electromagnetic 3D Modelling and Inversion." Exploration Geophysics 26, no. 2-3 (June 1, 1995): 138–43. http://dx.doi.org/10.1071/eg995138.

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Turunen, I., T. Nyberg, J. Järveläinen, Y. Y. Linko, P. Linko, and M. Dohnal. "Fuzzy modelling in biotechnology: Sucrose inversion." Chemical Engineering Journal 30, no. 3 (June 1985): B51—B60. http://dx.doi.org/10.1016/0300-9467(85)80028-9.

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Madden, T. M., and R. L. Mackie. "Three-dimensional magnetotelluric modelling and inversion." Proceedings of the IEEE 77, no. 2 (1989): 318–33. http://dx.doi.org/10.1109/5.18628.

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Xiaojuan, Li, Huang Mutao, and Li Jianbao. "Remote sensing inversion of lake water quality parameters based on ensemble modelling." E3S Web of Conferences 143 (2020): 02007. http://dx.doi.org/10.1051/e3sconf/202014302007.

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In this paper, combined with water quality sampling data and Landsat8 satellite remote sensing image data, the inversion model of Chl-a and TN water quality parameter concentration was constructed based on machine learning algorithm. After the verification and evaluation of the inversion results of the test samples, Chl-a TN inversion model with high correlation between model test results and measured data was selected to participate in remote sensing inversion ensemble modelling of water quality parameters. Then, the ensemble remote sensing inversion model of water quality parameters was established based on entropy weight method and error analysis. By applying the idea of ensemble modelling to remote sensing inversion of water quality parameters, the advantages of different models can be integrated and the precision of water quality parameters inversion can be improved. Through the evaluation and comparative analysis of the model results, the entropy weight method can improve the inversion accuracy to some extent, but the improvement space is limited. In the verification of the two methods of ensemble modelling based on error analysis, compared with the optimal results of a single model, the determination coefficient (R2) of Chlorophyll a and TN concentration inversion results was increased from 0.9288 to 0.9313 and from 0.8339 to 0.8838, and the root mean square error was decreased from 14.2615 μ/L to 10.4194 μ/L and from1.1002mg/L to 0.8621mg/L. At the same time, with the increase of the number of models involved in the set modelling, the inversion accuracy is higher.
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Giraud, Jeremie, Mark Lindsay, Vitaliy Ogarko, Mark Jessell, Roland Martin, and Evren Pakyuz-Charrier. "Integration of geoscientific uncertainty into geophysical inversion by means of local gradient regularization." Solid Earth 10, no. 1 (January 25, 2019): 193–210. http://dx.doi.org/10.5194/se-10-193-2019.

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Abstract. We introduce a workflow integrating geological modelling uncertainty information to constrain gravity inversions. We test and apply this approach to the Yerrida Basin (Western Australia), where we focus on prospective greenstone belts beneath sedimentary cover. Geological uncertainty information is extracted from the results of a probabilistic geological modelling process using geological field data and their inferred accuracy as inputs. The uncertainty information is utilized to locally adjust the weights of a minimum-structure gradient-based regularization function constraining geophysical inversion. Our results demonstrate that this technique allows geophysical inversion to update the model preferentially in geologically less certain areas. It also indicates that inverted models are consistent with both the probabilistic geological model and geophysical data of the area, reducing interpretation uncertainty. The interpretation of inverted models reveals that the recovered greenstone belts may be shallower and thinner than previously thought.
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RAMÍREZ, JOSÉ L., GUSTAVO N. RUBIANO, and BORUT JURČIČ ZLOBEC. "GENERATING FRACTAL PATTERNS BY USING p-CIRCLE INVERSION." Fractals 23, no. 04 (December 2015): 1550047. http://dx.doi.org/10.1142/s0218348x15500474.

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In this paper, we introduce the [Formula: see text]-circle inversion which generalizes the classical inversion with respect to a circle ([Formula: see text]) and the taxicab inversion [Formula: see text]. We study some basic properties and we also show the inversive images of some basic curves. We apply this new transformation to well-known fractals such as Sierpinski triangle, Koch curve, dragon curve, Fibonacci fractal, among others. Then we obtain new fractal patterns. Moreover, we generalize the method called circle inversion fractal be means of the [Formula: see text]-circle inversion.
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Wilson, Glenn, Art Raiche, and Fred Sugeng. "Practical 3D AEM inversion using 2.5D modelling." ASEG Extended Abstracts 2006, no. 1 (December 2006): 1–4. http://dx.doi.org/10.1071/aseg2006ab196.

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Dissertations / Theses on the topic "Inversion modelling"

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Yamada, Yasuhiro. "3D analogue modelling of inversion structures." Thesis, Royal Holloway, University of London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.311874.

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Ardjmandpour, Negah. "Modelling and Inversion of Array Induction tool." Thesis, Imperial College London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.522875.

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Millington, Timothy M. "Modelling and inversion of ground penetrating radar." Thesis, Keele University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540623.

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Zhang, Ai Jun. "Modelling and inversion of two-dimensional magnetotelluric data." Thesis, University of Edinburgh, 1988. http://hdl.handle.net/1842/14717.

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Lewi, Elias. "Modelling and inversion of high precision gravity data /." München : Bayerische Akademie der Wissenschaften, 1997. http://catalogue.bnf.fr/ark:/12148/cb409231411.

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Rücker, Carsten. "Advanced Electrical Resistivity Modelling and Inversion using Unstructured Discretization." Doctoral thesis, Universitätsbibliothek Leipzig, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-69066.

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In this dissertation an approach is presented for the three-dimensional electrical resistivity tomography (ERT) using unstructured discretizations. The geoelectrical forward problem is solved by the finite element method using tetrahedral meshes with linear and quadratic shape functions. Unstructured meshes are suitable for modelling domains of arbitrary geometry (e.g., complicated topography). Furthermore, the best trade-off between accuracy and numerical effort can be achieved due to the capability of problem-adapted mesh refinement. Unstructured discretizations also allow the consideration of spatial extended finite electrodes. Due to a corresponding extension of the forward operator using the complete electrode model, known from medical impedance tomography, a study about the influence of such electrodes to geoelectrical measurements is given. Based on the forward operator, the so-called triple-grid-technique is developed to solve the geoelectrical inverse problem. Due to unstructured discretization, the ERT can be applied by using a resolution dependent parametrization on arbitrarily shaped two-dimensional and three-dimensional domains. A~Gauss-Newton method is used with inexact line search to fit the data within error bounds. A global regularization scheme is applied using special smoothness constraints. Furthermore, an advanced regularization scheme for the ERT is presented based on unstructured meshes, which is able to include a-priori information into the inversion and significantly improves the resulting ERT images. Structural information such as material interfaces known from other geophysical techniques are incorporated as allowed sharp resistivity contrasts. Model weighting functions can define individually the allowed deviation of the final resistivity model from given start or reference values. As a consequent further development the region concept is presented where the parameter domain is subdivided into lithological or geological regions with individual inversion and regularization parameters. All used techniques and concepts are part of the open source C++ library GIMLi, which has been developed during this thesis as an advanced tool for the method-independent solution of the inverse problem.
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Tsourlos, Panagiotis. "Modelling, interpretation and inversion of multielectrode resistivity survey data." Thesis, University of York, 1995. http://etheses.whiterose.ac.uk/14017/.

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Stek, Ivan. "Frequency domain seismic forward modelling : a tool for waveform inversion." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267748.

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Vieira, da Silva Nuno Miguel. "Three-dimensional modelling and inversion of controlled source electromagnetic data." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/9120.

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The marine Controlled Source Electromagnetic (CSEM) method is an important and almost self-contained discipline in the toolkit of methods used by geophysicists for probing the earth. It has increasingly attracted attention from industry during the past decade due to its potential in detecting valuable natural resources such as oil and gas. A method for three-dimensional CSEM modelling in the frequency domain is presented. The electric field is decomposed in primary and secondary components, as this leads to a more stable solution near the source position. The primary field is computed using a resistivity model for which a closed form of solution exists, for example a homogeneous or layered resistivity model. The secondary electric field is computed by discretizing a second order partial differential equation for the electric field, also referred in the literature as the vector Helmholtz equation, using the edge finite element method. A range of methods for the solution of the linear system derived from the edge finite element discretization are investigated. The magnetic field is computed subsequently, from the solution for the electric field, using a local finite difference approximation of Faraday’s law and an interpolation method. Tests, that compare the solution obtained using the presented method with the solution computed using alternative codes for 1D and 3D synthetic models, show that the implemented approach is suitable for CSEM forward modelling and is an alternative to existing codes. An algorithm for 3D inversion of CSEM data in the frequency domain was developed and implemented. The inverse problem is solved using the L-BFGS method and is regularized with a smoothing constraint. The inversion algorithm uses the presented forward modelling scheme for the computation of the field responses and the adjoint field for the computation of the gradient of the misfit function. The presented algorithm was tested for a synthetic example, showing that it is capable of reconstructing a resistivity model which fits the synthetic data and is close to the original resistivity model in the least-squares sense. Inversion of CSEM data is known to lead to images with low spatial resolution. It is well known that integration with complementary data sets mitigates this problem. It is presented an algorithm for the integration of an acoustic velocity model, which is known a priori, in the inversion scheme. The algorithm was tested in a synthetic example and the results demonstrate that the presented methodology is promising for the improvement of resistivity models obtained from CSEM data.
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Yeo, Leslie Yu-Ming. "Modelling of phase inversion and associated phenomena in liquid-liquid systems." Thesis, University of London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.480683.

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Books on the topic "Inversion modelling"

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service), SpringerLink (Online, ed. Full Seismic Waveform Modelling and Inversion. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Fichtner, Andreas. Full Seismic Waveform Modelling and Inversion. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-15807-0.

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Weltje, G. J. Provenance and dispersal of sand-sized sediments: Reconstruction of dispersal patterns and sources of sand-sized sediments by means of inverse modelling techniques. [Utrecht: Faculteit Aardwetenschappen, Universiteit Utrecht, 1994.

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Habib, Ammari, Capdeboscq Yves 1971-, and Kang Hyeonbae, eds. Multi-scale and high-contrast PDE: From modelling, to mathematical analysis, to inversion : Conference on Multi-scale and High-contrast PDE:from Modelling, to Mathematical Analysis, to Inversion, June 28-July 1, 2011, University of Oxford, United Kingdom. Providence, R.I: American Mathematical Society, 2010.

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Continuous-time finance. Cambridge, Mass: B. Blackwell, 1992.

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Continuous-time finance. Cambridge, Mass: B. Blackwell, 1990.

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Fichtner, Andreas. Full Seismic Waveform Modelling and Inversion. Springer, 2013.

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Fichtner, Andreas. Full Seismic Waveform Modelling and Inversion. Springer, 2011.

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Berg, Simon Van Den. Modelling & Inversion of Pulsed Eddy Current Data. Delft Univ Pr, 2003.

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J, Götze H., Schmidt S, Maggio F, Serón F. J, Brown M. G, and Kotková J, eds. I. Modelling techniques and joint inversion in earth sciences. Oxford: Pergamon, 1999.

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Book chapters on the topic "Inversion modelling"

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Nanda, Niranjan C. "Seismic Modelling and Inversion." In Seismic Data Interpretation and Evaluation for Hydrocarbon Exploration and Production, 187–204. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26491-2_11.

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Nanda, Niranjan C. "Seismic Modelling and Inversion." In Seismic Data Interpretation and Evaluation for Hydrocarbon Exploration and Production, 223–41. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75301-6_11.

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Chen, Liangfu, Jin Chen, Guangjian Yan, Wenjie Fan, Xiaozhou Xin, Chaoyang Wu, Tianjie Zhao, Shenglei Zhang, and Xiaoying Li. "Remote Sensing Modelling and Parameter Inversion." In Springer Geography, 323–38. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1884-8_14.

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Fichtner, Andreas. "Preliminaries." In Full Seismic Waveform Modelling and Inversion, 1–5. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_1.

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Fichtner, Andreas. "The Frequency-Domain Discrete Adjoint Method." In Full Seismic Waveform Modelling and Inversion, 189–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_10.

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Fichtner, Andreas. "Misfit Functionals and Adjoint Sources." In Full Seismic Waveform Modelling and Inversion, 193–210. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_11.

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Fichtner, Andreas. "Fréchet and Hessian Kernel Gallery." In Full Seismic Waveform Modelling and Inversion, 211–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_12.

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Fichtner, Andreas. "Full Waveform Tomography on Continental Scales." In Full Seismic Waveform Modelling and Inversion, 233–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_13.

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Fichtner, Andreas. "Application of Full Waveform Tomography to Active-Source Surface-Seismic Data." In Full Seismic Waveform Modelling and Inversion, 267–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_14.

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Fichtner, Andreas. "Source Stacking Data Reduction for Full Waveform Tomography at the Global Scale." In Full Seismic Waveform Modelling and Inversion, 281–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_15.

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Conference papers on the topic "Inversion modelling"

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Yakovleva, I., and H. Debeye. "Fluid contacts modelling in geostatistical inversion." In Second EAGE Conference on Seismic Inversion. European Association of Geoscientists & Engineers, 2022. http://dx.doi.org/10.3997/2214-4609.202229024.

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Mesdag, P., C. Tanase, and H. Debeye. "Forward Modelling and Inversion with 3D Wavelets." In First EAGE Conference on Seismic Inversion. European Association of Geoscientists & Engineers, 2020. http://dx.doi.org/10.3997/2214-4609.202037009.

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"Radar data modelling and inversion." In 15th International Conference on Ground-Penetrating Radar (GPR) 2014. IEEE, 2014. http://dx.doi.org/10.1109/icgpr.2014.6970469.

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Loke, M. H. "Topographic Modelling in Electrical Imaging Inversion." In 62nd EAGE Conference & Exhibition. European Association of Geoscientists & Engineers, 2000. http://dx.doi.org/10.3997/2214-4609-pdb.28.d2.

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Mesdag, P., A. Edvardsen, I. Magnus, and H. Debeye. "Reservoir modelling using 3D inversion techniques." In EAEG/EAPG/EAGO Joint Multidisciplinary Workshop - Developing New Reservoirs in Europe. European Association of Geoscientists & Engineers, 1994. http://dx.doi.org/10.3997/2214-4609.201407008.

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Wu, Xiaoyang, Xiangyang Li, and Hengchang Dai. "Shale geophysical modelling and statistical inversion." In SEG Technical Program Expanded Abstracts 2019. Society of Exploration Geophysicists, 2019. http://dx.doi.org/10.1190/segam2019-3197892.1.

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Gunning, J., and M. E. Glinsky. "Error Modelling in Bayesian CSEM Inversion." In 72nd EAGE Conference and Exhibition incorporating SPE EUROPEC 2010. European Association of Geoscientists & Engineers, 2010. http://dx.doi.org/10.3997/2214-4609.201400737.

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Murineddu, A., J. Siupik, and C. Leone. "Single Loop Litho-Petro-Elastic Modelling and Inversion: An Example of Prospect Characterization in the Norwegian Sea." In First EAGE Conference on Seismic Inversion. European Association of Geoscientists & Engineers, 2020. http://dx.doi.org/10.3997/2214-4609.202037037.

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Leibniz, Thomas Günther,, and Carsten cker. "Advanced Inversion Strategies Using a New Geophysical Inversion and Modelling Library." In Symposium on the Application of Geophysics to Engineering and Environmental Problems 2010. Environment and Engineering Geophysical Society, 2010. http://dx.doi.org/10.4133/1.3445461.

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Günther, T., and C. Rücker. "Advanced Inversion Strategies Using a New Geophysical Inversion and Modelling Library." In Near Surface 2009 - 15th EAGE European Meeting of Environmental and Engineering Geophysics. European Association of Geoscientists & Engineers, 2009. http://dx.doi.org/10.3997/2214-4609.20147039.

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Reports on the topic "Inversion modelling"

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Ansari, M. Development of numerical modelling and inversion (optimization) algorithms for geophysical electromagnetic (EM) data. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329099.

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Goodwin, J. A., R. Hackney, and N. C. Williams. 3D geophysical inversion modelling of the Wallaby Plateau: evidence for continental crust and seaward-dipping reflectors. Geoscience Australia, 2015. http://dx.doi.org/10.11636/record.2015.001.

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Queralt, P., A. G. Jones, and J. Ledo. Deep electromagnetic imaging of the Bathurst No. 12 deposit, New Brunswick: three-dimensional forward modelling, two-dimensional inversion, and sensitivity tests. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2002. http://dx.doi.org/10.4095/213238.

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Goodwin, J. A., and R. J. L. Lane. The North Australian Craton 3D Gravity and Magnetic Inversion Models: A trial for first pass modelling of the entire Australian continent. Geoscience Australia, 2021. http://dx.doi.org/10.11636/record.2021.033.

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Ansari, S. M., E. M. Schetselaar, and J. A. Craven. Three-dimensional magnetotelluric modelling of the Lalor volcanogenic massive-sulfide deposit, Manitoba. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/328003.

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Unconstrained magnetotelluric inversion commonly produces insufficient inherent resolution to image ore-system fluid pathways that were structurally thinned during post-emplacement tectonic activity. To improve the resolution in these complex environments, we synthesized the 3-D magnetotelluric (MT) response for geologically realistic models using a finite-element-based forward-modelling tool with unstructured meshes and applied it to the Lalor volcanogenic massive-sulfide deposit in the Snow Lake mining camp, Manitoba. This new tool is based on mapping interpolated or simulated resistivity values from wireline logs onto unstructured tetrahedral meshes to reflect, with the help of 3-D models obtained from lithostratigraphic and lithofacies drillhole logs, the complexity of the host-rock geological structure. The resulting stochastic model provides a more realistic representation of the heterogeneous spatial distribution of the electric resistivity values around the massive, stringer, and disseminated sulfide ore zones. Both models were combined into one seamless tetrahedral mesh of the resistivity field. To capture the complex resistivity distribution in the geophysical forward model, a finite-element code was developed. Comparative analyses of the forward models with MT data acquired at the Earth's surface show a reasonable agreement that explains the regional variations associated with the host rock geological structure and detects the local anomalies associated with the MT response of the ore zones.
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Ansari, S. M., J. A. Craven, and E. Schetselaar. Three-dimensional forward modelling and inversion of magnetotelluric data using unstructured meshes for understanding realistic geological systems: method development, algorithms and model construction for the Lalor deposit, Manitoba. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2019. http://dx.doi.org/10.4095/313656.

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Goodwin, J. A., W. Jiang, A. J. Meixner, S. R. B. McAlpine, S. Buckerfield, M. G. Nicoll, and M. Crowe. Estimating cover thickness in the Southern Thomson Orogen: results from the pre-drilling application of refraction seismic, audio-magnetotelluric and targeted magnetic inversion modelling methods on proposed borehole sites. Geoscience Australia, 2017. http://dx.doi.org/10.11636/record.2017.021.

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8

Liu, X., Z. Chen, and S. E. Grasby. Using shallow temperature measurements to evaluate thermal flux anomalies in the southern Mount Meager volcanic area, British Columbia, Canada. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330009.

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Abstract:
Geothermal is a clean and renewable energy resource. However, locating where elevated thermal gradient anomalies exist is a significant challenge when trying to assess potential resource volumes during early exploration of a prospective geothermal area. In this study, we deployed 22 temperature probes in the shallow subsurface along the south flank of the Mount Meager volcanic complex, to measure the transient temperature variation from September 2020 to August 2021. In our data analysis, a novel approach was developed to estimate the near-surface thermal distribution, and a workflow and code with python language have been completed for the thermal data pre-processing and analysis. The long-term temperature variation at different depths can be estimated by modelling, so that the relative difference of deducing deeper geothermal gradient anomalies can be assessed. Our proposed inversion and simulation methods were applied to calculating the temperature variation at 2.0 meters depth. The results identified a preferred high thermal flux anomalous zone in the south Mount Meager area. By combining with previous studies, the direct analysis and estimation of anomalous thermal fields based on the collected temperature data can provide a significant reference for interpretation of the regional thermal gradient variation.
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