Transient electromagnetic search engine for real-time imaging

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. E277-E285 ◽  
Author(s):  
Jide Nosakare Ogunbo ◽  
Jie Zhang ◽  
Xiong Zhang
Keyword(s):  
Real Time ◽  
Search Engine ◽  
Solution Space ◽  
Inversion Method ◽  
Model Parameters ◽  
Transient Electromagnetic ◽  
Model Solutions ◽  
Resistivity Model ◽  
2D Resistivity ◽  
Engine Method

To image the resistivity distribution of the subsurface, transient electromagnetic (TEM) surveying has been established as an effective geophysical method. Conventionally, an inversion method is applied to resolve the model parameters from the available measurements. However, significant time and effort are involved in preparing and executing an inversion and this prohibits its use as a real-time decision-making tool to optimize surveying in the field. We have developed a search engine method to find approximate 1D resistivity model solutions for circular central-loop configuration TEM data in real time. The search engine method is a concept used for query searches from large databases on the Internet. By extension, approximate solutions to any input TEM data can be found rapidly by searching a preestablished database. This database includes a large number of forward simulation results that represent the possible model solutions. The database size is optimized by the survey depth of investigation and the sensitivity analysis of the model layers. The fast-search speed is achieved by using the multiple randomized [Formula: see text]-dimensional tree method. In addition to its high speed in finding solutions, the search engine method provides a solution space that quantifies the resolutions and uncertainties of the results. We apply the search engine method to find 1D model solutions at different data points and then interpolate them to a pseudo-2D resistivity model. We tested the method with synthetic and real data.

scholarly journals LWD DATA INVERSION FOR STRUCTURE WITH ANGULAR UNCONFORMITY

2021 ◽  
Vol 2 (1) ◽  
pp. 336-344
Author(s):  
Anna S. Astrakova ◽  
Elena V. Konobriy ◽  
Dmitry Yu. Kushnir ◽  
Nikolay N. Velker ◽  
Gleb V. Dyatlov
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Parametric Model ◽  
Model Parameters ◽  
Time Inversion ◽  
Water Contact ◽  
2D Inversion ◽  
Angular Unconformity ◽  
Oil Water ◽  
2D Resistivity

Non-structural traps and reservoir flanks are characterized by angular unconformities. Angular unconformity between dipping formation and sub-horizontal oil-water contact is common in the North Sea fields. This paper presents an approach to real-time inversion of LWD resistivity data for the scenario with angular unconformity. The approach utilizes artificial neural networks (ANNs) for calculating the tool responses in parametric surface-based 2D resistivity models. We propose a parametric model with two non-parallel boundaries suitable for scenarios with angular unconformity and pinch-out. Training of ANNs for this parametric model is performed using a database containing samples with the model parameters and corresponding tool responses. ANNs are the kernel of 2D inversion based on the Levenberg-Marquardt optimization method. To demonstrate applicability of our approach and compare with the results of 1D inversion, we analyze Extra Deep Azimuthal Resistivity tool responses in a 2D synthetic model. It is shown that 1D inversion determines either the position of the oil-water contact or dipping layers structure. At the same time, 2D inversion makes it possible to correctly reconstruct the positions of non-parallel boundaries. Performance of 2D inversion based on ANNs is suitable for real-time applications.

Microseismic search engine for real-time estimation of source location and focal mechanism

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. KS169-KS182 ◽  
Author(s):  
Xiong Zhang ◽  
Jie Zhang
Keyword(s):  
Hydraulic Fracturing ◽  
Real Time ◽  
Search Engine ◽  
Focal Mechanism ◽  
Input Data ◽  
Web Search ◽  
Solution Space ◽  
Web Search Engine ◽  
Fracturing Process ◽  
Microseismic Events

Similar to a web search engine, we have developed a microseismic search engine that can estimate an event location and the focal mechanism in less than a second to monitor the hydraulic fracturing process. The method was extended from a real-time earthquake monitoring approach for seismological applications. We first calculate the full waveforms of all possible microseismic events over a 3D grid with a known velocity model for a given acquisition geometry to create a database. We then index and rank all of the seismic waveforms in the database by following the characteristics of the phase and amplitude of the waveform through a computer fast search technology, specifically, the multiple randomized k-dimensional tree method. When a microseismic event occurs, the approximate best matches to the entry waveform are found immediately by comparing the characteristic features between the input data and the database. The method returns not just one but a series of solutions, similar to a web search engine. Thus, we can obtain a solution space that delineates the resolution and confidence level of the results. Also similar to a web search engine, the microseismic search engine does not require any input parameter or processing experience; thus, the solutions are the same for any user. Numerical tests suggest that the waveform search approach is insensitive to random and correlated noises. However, if the correlation values between the input data and best matches in the database are too low, suggesting unreliable results, the solution may be rejected automatically by applying a preset threshold. We have applied the method to real data, and found great potential for the routine real-time monitoring of microseismic events during hydraulic fracturing.

scholarly journals Real-time earthquake monitoring using a search engine method

2014 ◽  
Vol 5 (1) ◽  
Author(s):  
Jie Zhang ◽  
Haijiang Zhang ◽  
Enhong Chen ◽  
Yi Zheng ◽  
Wenhuan Kuang ◽  
...  
Keyword(s):  
Real Time ◽  
Search Engine ◽  
Earthquake Monitoring ◽  
Engine Method

Multiscale resistivity inversion based on convolutional wavelet transform

2020 ◽  
Vol 223 (1) ◽  
pp. 132-143 ◽  
Author(s):  
Yonghao Pang ◽  
Lichao Nie ◽  
Bin Liu ◽  
Zhengyu Liu ◽  
Ning Wang
Keyword(s):  
Wavelet Transform ◽  
A Priori ◽  
Geophysical Methods ◽  
Spatial Domain ◽  
Inversion Method ◽  
Model Parameters ◽  
Imaging Method ◽  
Feature Parameters ◽  
Resistivity Model ◽  
Resistivity Inversion

SUMMARY The resistivity imaging method, an effective geophysical technique, has been widely used in environmental, engineering and hydrological fields. The inversion method based on smooth constraint is one of the most commonly used methods. However, this method causes the resistivity to change smoothly and makes it difficult to describe geological boundaries accurately. An accurate description of the target's boundaries often requires a priori information gained with other methods (such as other geophysical methods or geological drilling). To address this issue, a multiscale inversion method is proposed for extracting boundary features and inverting feature parameters from different scales. In this method, a convolution kernel is used to extract the boundary information from the resistivity model. The model parameters are transformed from the spatial domain to the feature domain via a convolutional wavelet transform. The feature parameters of different scales can then be obtained by solving the inversion equation in the feature domain. After that, the resistivity model of the spatial domain is reconverted from the feature domain by deconvolution transform of the inversion result. Numerical simulations and experiments show that the new multiscale resistivity inversion method has the ability to locate and depict boundaries of geological targets with high accuracy.

scholarly journals Real-time automatic uncertainty estimation of coseismic single rectangular fault model using GNSS data

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Keitaro Ohno ◽  
Yusaku Ohta ◽  
Satoshi Kawamoto ◽  
Satoshi Abe ◽  
Ryota Hino ◽  
...  
Keyword(s):  
Real Time ◽  
Disaster Response ◽  
Order Approximation ◽  
Nonlinear Problems ◽  
Large Earthquake ◽  
Fault Model ◽  
Deformation Monitoring ◽  
Model Parameters ◽  
The Sea Of Japan ◽  
Plate Interface

AbstractRapid estimation of the coseismic fault model for medium-to-large-sized earthquakes is key for disaster response. To estimate the coseismic fault model for large earthquakes, the Geospatial Information Authority of Japan and Tohoku University have jointly developed a real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD can estimate the single rectangular fault model and slip distribution along the assumed plate interface. The single rectangular fault model is useful as a first-order approximation of a medium-to-large earthquake. However, in its estimation, it is difficult to obtain accurate results for model parameters due to the strong effect of initial values. To solve this problem, this study proposes a new method to estimate the coseismic fault model and model uncertainties in real time based on the Bayesian inversion approach using the Markov Chain Monte Carlo (MCMC) method. The MCMC approach is computationally expensive and hyperparameters should be defined in advance via trial and error. The sampling efficiency was improved using a parallel tempering method, and an automatic definition method for hyperparameters was developed for real-time use. The calculation time was within 30 s for 1 × 106 samples using a typical single LINUX server, which can implement real-time analysis, similar to REGARD. The reliability of the developed method was evaluated using data from recent earthquakes (2016 Kumamoto and 2019 Yamagata-Oki earthquakes). Simulations of the earthquakes in the Sea of Japan were also conducted exhaustively. The results showed an advantage over the maximum likelihood approach with a priori information, which has initial value dependence in nonlinear problems. In terms of application to data with a small signal-to-noise ratio, the results suggest the possibility of using several conjugate fault models. There is a tradeoff between the fault area and slip amount, especially for offshore earthquakes, which means that quantification of the uncertainty enables us to evaluate the reliability of the fault model estimation results in real time.

scholarly journals Enhanced Neural Network Model for Worldwide Estimation of Weighted Mean Temperature

2021 ◽  
Vol 13 (12) ◽  
pp. 2405
Author(s):  
Fengyang Long ◽  
Chengfa Gao ◽  
Yuxiang Yan ◽  
Jinling Wang
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Model Performance ◽  
Global Scale ◽  
Radiosonde Data ◽  
Model Parameters ◽  
Measured Temperature ◽  
Weighted Mean ◽  
Weighted Mean Temperature ◽  
Application Scope

Precise modeling of weighted mean temperature (Tm) is critical for realizing real-time conversion from zenith wet delay (ZWD) to precipitation water vapor (PWV) in Global Navigation Satellite System (GNSS) meteorology applications. The empirical Tm models developed by neural network techniques have been proved to have better performances on the global scale; they also have fewer model parameters and are thus easy to operate. This paper aims to further deepen the research of Tm modeling with the neural network, and expand the application scope of Tm models and provide global users with more solutions for the real-time acquisition of Tm. An enhanced neural network Tm model (ENNTm) has been developed with the radiosonde data distributed globally. Compared with other empirical models, the ENNTm has some advanced features in both model design and model performance, Firstly, the data for modeling cover the whole troposphere rather than just near the Earth’s surface; secondly, the ensemble learning was employed to weaken the impact of sample disturbance on model performance and elaborate data preprocessing, including up-sampling and down-sampling, which was adopted to achieve better model performance on the global scale; furthermore, the ENNTm was designed to meet the requirements of three different application conditions by providing three sets of model parameters, i.e., Tm estimating without measured meteorological elements, Tm estimating with only measured temperature and Tm estimating with both measured temperature and water vapor pressure. The validation work is carried out by using the radiosonde data of global distribution, and results show that the ENNTm has better performance compared with other competing models from different perspectives under the same application conditions, the proposed model expanded the application scope of Tm estimation and provided the global users with more choices in the applications of real-time GNSS-PWV retrival.

scholarly journals Transient ICD malfunctions during oncologic radiotherapy: a multi-centre, randomized, in-vitro study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
E Di Girolamo ◽  
M Appignani ◽  
N Furia ◽  
M Marini ◽  
P De Filippo ◽  
...  
Keyword(s):  
Real Time ◽  
Treatment Plan ◽  
Low Energy ◽  
In Vivo Dosimetry ◽  
Implantable Cardioverter Defibrillators ◽  
Shock Delivery ◽  
Transient Electromagnetic ◽  
Direct Exposure

Abstract Background Direct exposure of implantable cardioverter-defibrillators (ICDs) during radiotherapy is still considered potentially harmful, or even unsafe, by manufacturers and current recommendations. The effects of photon beams on ICDs are unpredictable, depending on multiple factors, and malfunctions may present during exposure. Purpose To evaluate transient ICD malfunctions by direct exposure to doses up to 10 Gy during low-energy RT, forty-three contemporary wireless-enabled ICDs, with at least 4 months to elective replacement indicator (ERI) were evaluated in a real-time in-vitro session in three different centres. Methods All ICDs had baseline interrogation. Single chamber devices were programmed to the VVI/40 mode and dual or triple chamber devices were programmed to the DDD/40 mode. Rate response function and antitachycardia therapies were disabled, with the ventricular tachycardia (VT)/ventricular fibrillation (VF) detection windows still active. A centring computed tomography was performed to build the corresponding treatment plan and the ICDs were blinded randomized to receive either 2-, 5- or 10-Gy exposure by a low photon-energy linear accelerator (6MV) in a homemade water phantom (600 MU/min). The effective dose received by the ICDs was randomly assessed by an in-vivo dosimetry. During radiotherapy, the ICDs were observed in a real-time session using manufacturer specific programmer, and device function (pacing, sensing, programmed parameters, arrhythmia detections) was recorder by the video camera in the bunker throughout the entire photon exposure. All ICDs had an interrogation session immediately after exposure. Results During radiotherapy course, almost all ICDs (93%) recorded major or minor transient electromagnetic interferences. On detail, sixteen ICDs (37.2%) reported atrial and/or ventricular oversensing, with base-rate-pacing inhibition and VT/VF detection. Twenty-four ICDs (55.8%) recorded non clinically relevant noise, and no detections were observed. Only three ICDs (7%) reported neither transient malfunction nor minor noise, withstanding direct radiation exposure. At immediate post-exposure interrogation, the ICDs that recorded major real-time malfunctions had VT/VF detections stored in the device memory. In none of the ICDs spontaneous changes in parameter settings were reported. Malfunctions occurred regardless of either 2-, 5- or 10-Gy photon beam exposure. Conclusions Transient electromagnetic interferences were observed in most of the contemporary ICDs during radiotherapy course, regardless of photon dose. To avoid potentially life-threatening ICD malfunctions such as pacing inhibition or inappropriate shock delivery, magnet application on the pocket site or ICD reprogramming to the asynchronous mode are still suggested in ICD patients ongoing even low energy radiotherapy exposure. Funding Acknowledgement Type of funding source: None

scholarly journals Experimental Verification of Real-Time Flow-Rate Estimations in a Tilting-Ladle-Type Automatic Pouring Machine

2021 ◽  
Vol 11 (15) ◽  
pp. 6701
Author(s):  
Yuta Sueki ◽  
Yoshiyuki Noda
Keyword(s):  
Real Time ◽  
Molten Metal ◽  
Flow Rate ◽  
Kalman Filters ◽  
Estimation Method ◽  
Estimation Methods ◽  
Liquid Volume ◽  
Model Parameters ◽  
Rate Estimation ◽  
Time Flow

This paper discusses a real-time flow-rate estimation method for a tilting-ladle-type automatic pouring machine used in the casting industry. In most pouring machines, molten metal is poured into a mold by tilting the ladle. Precise pouring is required to improve productivity and ensure a safe pouring process. To achieve precise pouring, it is important to control the flow rate of the liquid outflow from the ladle. However, due to the high temperature of molten metal, directly measuring the flow rate to devise flow-rate feedback control is difficult. To solve this problem, specific flow-rate estimation methods have been developed. In the previous study by present authors, a simplified flow-rate estimation method was proposed, in which Kalman filters were decentralized to motor systems and the pouring process for implementing into the industrial controller of an automatic pouring machine used a complicatedly shaped ladle. The effectiveness of this flow rate estimation was verified in the experiment with the ideal condition. In the present study, the appropriateness of the real-time flow-rate estimation by decentralization of Kalman filters is verified by comparing it with two other types of existing real-time flow-rate estimations, i.e., time derivatives of the weight of the outflow liquid measured by the load cell and the liquid volume in the ladle measured by a visible camera. We especially confirmed the estimation errors of the candidate real-time flow-rate estimations in the experiments with the uncertainty of the model parameters. These flow-rate estimation methods were applied to a laboratory-type automatic pouring machine to verify their performance.

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