On the Influence of 3-D structures in the Interpretation of transient electromagnetic sounding data

Geophysics ◽  
1994 ◽  
Vol 59 (6) ◽  
pp. 889-901 ◽  
Author(s):  
Mark Goldman ◽  
Leonty Tabarovsky ◽  
Michael Rabinovich
Keyword(s):  
Field Data ◽  
Synthetic Data ◽  
Real Field ◽  
Good Reliability ◽  
Electromagnetic Sounding ◽  
Transient Electromagnetic ◽  
Long Offset ◽  
Near Zone ◽  
Two Layer Model ◽  
Central Loop

The limitations of a standard 1-D inversion applied to multidimensional (synthetic) data are investigated. Simple correction procedures for interpreting field data distorted by 3-D structures are suggested. Two different transmitter/receiver configurations of the transient electromagnetic (TEM) sounding method are examined: a central loop configuration for the near zone (sometimes called short offset) and a fixed transmitter/moving receiver configuration for the far zone (long offset). The 3-D models are structural depressions and highs in both resistive and conductive basements. The fixed transmitter (grounded dipole) in the long offset TEM configuration is located at a distance significantly greater than both the size and depth of the structure. In all cases, 1-D interpretation of the central loop soundings recovers geoelectric parameters of the section with good reliability, although fictitious layers may appear near vertical boundaries. The 1-D interpretation of long offset soundings does not, in most cases, show the actual structures. The data along various profiles are interpreted in terms of a two‐layer model without the structures. In some cases 1-D interpretation does show the structure, but the errors are far greater than those obtained in the inversion of central loop soundings. In all cases considered, the distortion of central loop soundings caused by 3-D effects is systematic and could, therefore, be corrected by simple procedures. These procedures permit interpretation of real field data that were previously abandoned owing to the strong distortions by lateral inhomogeneities.

Effects of electrical anisotropy on long-offset transient electromagnetic data

2020 ◽  
Vol 222 (2) ◽  
pp. 1074-1089 ◽  
Author(s):  
Yajun Liu ◽  
Pritam Yogeshwar ◽  
Xiangyun Hu ◽  
Ronghua Peng ◽  
Bülent Tezkan ◽  
...  
Keyword(s):  
Electric Field ◽  
Field Data ◽  
Large Scale ◽  
Mining Area ◽  
Black Shales ◽  
Electrical Anisotropy ◽  
Anisotropic Models ◽  
Data Inversion ◽  
Transient Electromagnetic ◽  
Long Offset

SUMMARY Electrical anisotropy of formations has been long recognized by field and laboratory evidence. However, most interpretations of long-offset transient electromagnetic (LOTEM) data are based on the assumption of an electrical isotropic earth. Neglecting electrical anisotropy of formations may cause severe misleading interpretations in regions with strong electrical anisotropy. During a large scale LOTEM survey in a former mining area in Eastern Germany, data was acquired over black shale formations. These black shales are expected to produce a pronounced bulk anisotropy. Here, we investigate the effects of electrical anisotropy on LOTEM responses through numerical simulation using a finite-volume time-domain (FVTD) algorithm. On the basis of isotropic models obtained from LOTEM field data, various anisotropic models are developed and analysed. Numerical results demonstrate that the presence of electrical anisotropy has a significant influence on LOTEM responses. Based on the numerical modelling results, an isolated deep conductive anomaly presented in the 2-D isotropic LOTEM electric field data inversion result is identified as a possible artifact introduced by using an isotropic inversion scheme. Trial-and-error forward modelling of the LOTEM electric field data using an anisotropic conductivity model can explain the data and results in a reasonable quantitative data fit. The derived anisotropic 2-D model is consistent with the prior geological information.

Understanding LOTEM data from mountainous terrain

Geophysics ◽  
2000 ◽  
Vol 65 (4) ◽  
pp. 1113-1123 ◽  
Author(s):  
Andreas Hördt ◽  
Martin Müller
Keyword(s):  
Field Data ◽  
Electromagnetic Coupling ◽  
Theoretical Data ◽  
Correction Method ◽  
Topographic Effects ◽  
Mountainous Terrain ◽  
Large Loop ◽  
Transient Electromagnetic ◽  
Conductivity Structure ◽  
Long Offset

Long‐offset transient electromagnetic (LOTEM) data from the Vesuvius volcano, in Italy, show that the EM response of the topography is a potential cause of data distortions. A modeling study was carried out to simulate the effect of mountainous terrain on vertical magnetic‐field time derivatives using a 3-D finite‐difference code. The objectives were to assess the importance of topographic effects and to help identify them in existing field data. The total effect of topography on the LOTEM response can be considered as a combination of four distortions of the corresponding responses for a flat terrain. First, the receiver is at some height above the flat surface. Second, the mountain acts as a conductive body displacing air. Third, large loop receivers are nonhorizontal and sense a combination of horizontal and vertical magnetic fields. Finally, the electromagnetic coupling between the mountain and deeper‐lying structure modifies the structure response. Each of the effects can be identified in field data recorded at Mount Vesuvius. The topographic induced distortions for the model used in this study are moderate in the sense that 1-D inversions of the theoretical data still recover the gross conductivity structure, albeit with small deviations from the true parameters. Although this result might imply that topography might be ignored during the first stage of an interpretation, no simple correction method is evident, so topography will have to be included in any 2-D or 3-D inversion attempt.

A quantitative appraisal of airborne and ground‐based transient electromagnetic (TEM) measurements in Denmark

Geophysics ◽  
2003 ◽  
Vol 68 (2) ◽  
pp. 523-534 ◽  
Author(s):  
Anders Vest Christiansen ◽  
Niels Bøie Christensen
Keyword(s):  
Field Data ◽  
Synthetic Data ◽  
Quantitative Model ◽  
Field Amplitude ◽  
One Dimensional ◽  
Transient Electromagnetic ◽  
Resolution Capability ◽  
Maximum Penetration ◽  
Quantitative Appraisal ◽  
Distorted Data

The last decade has seen growing use of ground‐based transient electromagnetic (TEM) methods in Denmark for hydrogeological purposes. Due to an intensified mapping campaign, airborne TEM methods were proposed as a possible tool for mapping large areas. The first test flights were flown in June 2000 using the GEOTEM system. Traditional approximate interpretation tools for airborne data are insufficient in hydrogeological investigations where a quantitative model specifying model parameter reliability is needed. We have carried out full nonlinear one‐dimensional inversion on the field amplitude of airborne synthetic and field data and compared the airborne method with the traditional ground‐based PROTEM 47 system that has found extensive use in Denmark. An improved measuring procedure for airborne systems is suggested to facilitate the estimation of noise that is necessary in a quantitative inversion. The analyses of synthetic data demonstrate the differences in resolution capability between ground‐based and airborne data. Ground‐based data typically resolve three‐ or four‐layer models and occasionally up to five layers. Airborne data resolve three layers as a maximum, one or two layers being common. The airborne GEOTEM system detects layers to depths of more than 300 m, bearing only little information about the top 50–70 m. The ground‐based PROTEM 47 system has a maximum penetration of approximately 170 m, with higher resolution capabilities in the top 100 m. Coupling to man‐made conductors is a serious problem for all TEM methods in densely populated areas and results in distorted data. Coupling influences the airborne data from Denmark on two‐thirds of the area covered. These data must be eliminated to avoid misinterpretation.

scholarly journals New Hybrid Approach for Developing Automated Machine Learning Workflows: A Real Case Application in Evaluation of Marcellus Shale Gas Production

Fuels ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 286-303
Author(s):  
Vuong Van Pham ◽  
Ebrahim Fathi ◽  
Fatemeh Belyadi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Shale Gas ◽  
Field Data ◽  
Marcellus Shale ◽  
Hybrid Approach ◽  
Gas Production ◽  
Bayesian Optimization ◽  
Real Field ◽  
Engineering Problems

The success of machine learning (ML) techniques implemented in different industries heavily rely on operator expertise and domain knowledge, which is used in manually choosing an algorithm and setting up the specific algorithm parameters for a problem. Due to the manual nature of model selection and parameter tuning, it is impossible to quantify or evaluate the quality of this manual process, which in turn limits the ability to perform comparison studies between different algorithms. In this study, we propose a new hybrid approach for developing machine learning workflows to help automated algorithm selection and hyperparameter optimization. The proposed approach provides a robust, reproducible, and unbiased workflow that can be quantified and validated using different scoring metrics. We have used the most common workflows implemented in the application of artificial intelligence (AI) and ML in engineering problems including grid/random search, Bayesian search and optimization, genetic programming, and compared that with our new hybrid approach that includes the integration of Tree-based Pipeline Optimization Tool (TPOT) and Bayesian optimization. The performance of each workflow is quantified using different scoring metrics such as Pearson correlation (i.e., R2 correlation) and Mean Square Error (i.e., MSE). For this purpose, actual field data obtained from 1567 gas wells in Marcellus Shale, with 121 features from reservoir, drilling, completion, stimulation, and operation is tested using different proposed workflows. A proposed new hybrid workflow is then used to evaluate the type well used for evaluation of Marcellus shale gas production. In conclusion, our automated hybrid approach showed significant improvement in comparison to other proposed workflows using both scoring matrices. The new hybrid approach provides a practical tool that supports the automated model and hyperparameter selection, which is tested using real field data that can be implemented in solving different engineering problems using artificial intelligence and machine learning. The new hybrid model is tested in a real field and compared with conventional type wells developed by field engineers. It is found that the type well of the field is very close to P50 predictions of the field, which shows great success in the completion design of the field performed by field engineers. It also shows that the field average production could have been improved by 8% if shorter cluster spacing and higher proppant loading per cluster were used during the frac jobs.

scholarly journals Photovoltaic Prediction Software: Evaluation with Real Data from Northern Spain

2021 ◽  
Vol 11 (11) ◽  
pp. 5025
Author(s):  
David González-Peña ◽  
Ignacio García-Ruiz ◽  
Montserrat Díez-Mediavilla ◽  
Mª. Isabel Dieste-Velasco ◽  
Cristina Alonso-Tristán
Keyword(s):  
Energy Production ◽  
Field Data ◽  
Real Data ◽  
Software Tools ◽  
Horizontal Axis ◽  
Real Field ◽  
Tracking Systems ◽  
Northern Spain ◽  
Commercial Software ◽  
Solar Tracking

Prediction of energy production is crucial for the design and installation of PV plants. In this study, five free and commercial software tools to predict photovoltaic energy production are evaluated: RETScreen, Solar Advisor Model (SAM), PVGIS, PVSyst, and PV*SOL. The evaluation involves a comparison of monthly and annually predicted data on energy supplied to the national grid with real field data collected from three real PV plants. All the systems, located in Castile and Leon (Spain), have three different tilting systems: fixed mounting, horizontal-axis tracking, and dual-axis tracking. The last 12 years of operating data, from 2008 to 2020, are used in the evaluation. Although the commercial software tools were easier to use and their installations could be described in detail, their results were not appreciably superior. In annual global terms, the results hid poor estimations throughout the year, where overestimations were compensated by underestimated results. This fact was reflected in the monthly results: the software yielded overestimates during the colder months, while the models showed better estimates during the warmer months. In most studies, the deviation was below 10% when the annual results were analyzed. The accuracy of the software was also reduced when the complexity of the dual-axis solar tracking systems replaced the fixed installation.

Integrity Assurance of an Oil Transportation Pipeline in a Transformed Design Environment

2015 ◽  
Author(s):  
Amitabh Kumar ◽  
Brian McShane ◽  
Mark McQueen
Keyword(s):  
Field Data ◽  
Oil And Gas ◽  
High Reliability ◽  
Complex Loading ◽  
Calibration Method ◽  
Real Field ◽  
Design Environment ◽  
Data Feedback ◽  
Integrity Management

A large Oil and Gas pipeline gathering system is commonly used to transport processed oil and gas from an offshore platform to an onshore receiving facility. High reliability and integrity for continuous operation of these systems is crucial to ensure constant supply of hydrocarbon to the onshore processing facility and eventually to market. When such a system is exposed to a series of complex environmental loadings, it is often difficult to predict the response path, in-situ condition and therefore the system’s ability to withstand subsequent future loading scenarios. In order to continue to operate the pipeline after a significant environmental event, an overall approach needs to be developed to — (a) Understand the system loading and the associated integrity, (b) Develop a series of criteria staging the sequence of actions following an event that will verify the pipeline integrity and (c) Ensure that the integrity management solution is simple and easy to understand so that it can be implemented consistently. For a complex loading scenario, one of the main challenges is the ability to predict the controlling parameter(s) that drives the global integrity of these systems. In such scenarios, the presence of numerous parameters makes the technical modeling and prediction tasks arduous. To address such scenarios, first and foremost, it is crucial to understand the baseline environment data and other associated critical design input elements. If the “design environmental baseline” has transformed (due to large events e.g. storms etc.) from its original condition; it modifies the dynamics of the system. To address this problem, a thorough modeling and assessment of the in-situ condition is essential. Further, a robust calibration method is required to predict the future response path and therefore expected pipeline condition. The study further compares the planned integrity management solutions to the field data to validate the efficiency of the predicted scenarios. By the inclusion of real field-data feedback to the modeling method, balanced integrity solutions can be achieved and the ability to quantify the risks is made more practical and actionable.

scholarly journals Coupled hydrogeophysical parameter estimation using a sequential Bayesian approach

2010 ◽  
Vol 14 (3) ◽  
pp. 545-556 ◽  
Author(s):  
J. Rings ◽  
J. A. Huisman ◽  
H. Vereecken
Keyword(s):  
Water Content ◽  
Particle Filtering ◽  
Field Data ◽  
Synthetic Data ◽  
Time Domain Reflectometry ◽  
Second Step ◽  
Parameter Estimates ◽  
Posterior Distributions ◽  
Data Set ◽  
Resistivity Tomography

Abstract. Coupled hydrogeophysical methods infer hydrological and petrophysical parameters directly from geophysical measurements. Widespread methods do not explicitly recognize uncertainty in parameter estimates. Therefore, we apply a sequential Bayesian framework that provides updates of state, parameters and their uncertainty whenever measurements become available. We have coupled a hydrological and an electrical resistivity tomography (ERT) forward code in a particle filtering framework. First, we analyze a synthetic data set of lysimeter infiltration monitored with ERT. In a second step, we apply the approach to field data measured during an infiltration event on a full-scale dike model. For the synthetic data, the water content distribution and the hydraulic conductivity are accurately estimated after a few time steps. For the field data, hydraulic parameters are successfully estimated from water content measurements made with spatial time domain reflectometry and ERT, and the development of their posterior distributions is shown.

Sign in / Sign up

Export Citation Format

Share Document