scholarly journals On coincident loop transient electromagnetic induction logging

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. E211-E220 ◽  
Author(s):  
Andrei Swidinsky ◽  
Chester J. Weiss
Keyword(s):  
Apparent Resistivity ◽  
Earth Model ◽  
Late Time ◽  
Concentric Cylinder ◽  
Transient Electromagnetic ◽  
Water Based ◽  
Resistivity Logs ◽  
Invasion Models ◽  
Whole Space ◽  
Formation Resistivity

Coincident loop transient induction wireline logging is examined as the borehole analog of the well-known land and airborne time-domain electromagnetic (EM) method. The concept of whole-space late-time apparent resistivity is modified from the half-space version commonly used in land and airborne geophysics and applied to the coincident loop voltages produced from various formation, borehole, and invasion models. Given typical tool diameters, off-time measurements with such an instrument must be made on the order of nanoseconds to microseconds — much more rapidly than for surface methods. Departure curves of the apparent resistivity for thin beds, calculated using an algorithm developed to model the transient response of a loop in a multilayered earth, indicate that the depth of investigation scales with the bed thickness. Modeled resistivity logs are comparable in accuracy and resolution with standard frequency-domain focused induction logs. However, if measurement times are longer than a few microseconds, the thicknesses of conductors can be overestimated, whereas resistors are underestimated. Thin-bed resolution characteristics are explained by visualizing snapshots of the EM fields in the formation, where a conductor traps the electric field while two current maxima are produced in the shoulder beds surrounding a resistor. Radial profiling is studied using a concentric cylinder earth model. Results found that true formation resistivity can be determined in the presence of either oil- or water-based mud, although in the latter case, measurements must be taken several orders of magnitude later in time. The ability to determine true formation resistivity is governed by the degree that the EM field heals after being distorted by borehole fluid and invasion, a process visualized and particularly evident in the case of conductive water-based mud.

The use and misuse of apparent resistivity in electromagnetic methods

Geophysics ◽  
1986 ◽  
Vol 51 (7) ◽  
pp. 1462-1471 ◽  
Author(s):  
Brian R. Spies ◽  
Dwight E. Eggers
Keyword(s):  
Apparent Resistivity ◽  
Early Time ◽  
Asymptotic Formulas ◽  
Voltage Response ◽  
Late Time ◽  
Induced Voltage ◽  
Resistivity Curve ◽  
Transient Electromagnetic ◽  
Electromagnetic Methods ◽  
Tem Method

Problems and misunderstandings arise with the concept of apparent resistivity when the analogy between an apparent resistivity computed from geophysical observations and the true resistivity structure of the subsurface is drawn too tightly. Several definitions of apparent resistivity are available for use in electromagnetic methods; however, those most commonly used do not always exhibit the best behavior. Many of the features of the apparent resistivity curve which have been interpreted as physically significant with one definition disappear when alternative definitions are used. It is misleading to compare the detection or resolution capabilities of different field systems or configurations solely on the basis of the apparent resistivity curve. For the in‐loop transient electromagnetic (TEM) method, apparent resistivity computed from the magnetic field response displays much better behavior than that computed from the induced voltage response. A comparison of “exact” and “asymptotic” formulas for the TEM method reveals that automated schemes for distinguishing early‐time and late‐time branches are at best tenuous, and those schemes are doomed to failure for a certain class of resistivity structures (e.g., the loop size is large compared to the layer thickness). For the magnetotelluric (MT) method, apparent resistivity curves defined from the real part of the impedance exhibit much better behavior than curves based on the conventional definition that uses the magnitude of the impedance. Results of using this new definition have characteristics similar to apparent resistivity obtained from time‐domain processing.

A single apparent resistivity expression for long‐offset transient electromagnetics

Geophysics ◽  
1986 ◽  
Vol 51 (6) ◽  
pp. 1291-1297 ◽  
Author(s):  
Yang Sheng
Keyword(s):  
Apparent Resistivity ◽  
Early Time ◽  
Point Of View ◽  
Time Range ◽  
Late Time ◽  
Careful Study ◽  
Physical Point ◽  
Layered Earth ◽  
Transient Electromagnetic ◽  
Long Offset

Early‐time and late‐time apparent resistivity approximations have been widely used for interpretation of long‐offset transient electromagnetic (LOTEM) measurements because it is difficult to find a single apparent resistivity over the whole time range. From a physical point of view, Dr. C. H. Stoyer defined an apparent resistivity for the whole time range. However, there are two problems which hinder its use: one is that there is no explicit formula to calculate the apparent resistivity, and the other is that the apparent resistivity has no single solution. A careful study of the two problems shows that a numerical method can be used to calculate a single apparent resistivity. A formula for the maximum receiver voltage over a uniform earth, when compared with the receiver voltage for a layered earth, leads to the conclusion that, in some cases, a layered earth can produce a larger voltage than any uniform earth can produce. Therefore, our apparent resistivity definition cannot be applied to those cases. In some other cases, the two possible solutions from our definition do not merge, so that neither of them is meaningful for the whole time range.

Transient electromagnetic modeling of shallow A‐type sections with 3-D inhomogeneities

Geophysics ◽  
1992 ◽  
Vol 57 (6) ◽  
pp. 774-780 ◽  
Author(s):  
M. Poddar ◽  
Walter L. Anderson
Keyword(s):  
Apparent Resistivity ◽  
Middle Layer ◽  
Late Time ◽  
Geoelectric Section ◽  
Resistivity Sounding ◽  
Transient Electromagnetic ◽  
Target Layer ◽  
Weathered Layer ◽  
Target Depth ◽  
Transient Electric Field

A hard rock area underlain by granitic/gneissic or basaltic rocks often has an A‐type three‐layer geoelectric section in which resistivity increases with depth. The middle layer of moderate resistivity caused by fracturing/fissuring that lies between the surface‐weathered layer and the substratum of unfractured rock is not a good target for a direct current (DC) resistivity sounding since it is generally suppressed in the observations. Moreover, its definition requires expanding the electrode spacing to a length several times the depth of the target layer, and this may be a drawback if the target layer is either laterally variable or limited in its horizontal extent. We first studied the transient electric field of a horizontal electric dipole (HED) source excited by a step turn‐off current for a 1-D model of an A‐type geoelectric section. The results of this theoretical study are presented as graphs of normalized apparent resistivity versus a time‐related dimensionless parameter. Irrespective of the separation between the transmitter and receiver dipoles, these transient sounding curves become similar to the corresponding Schlumberger sounding curves at late time. Hence the transient electric field measurement offers the possibility of sounding at a fixed transmitter‐receiver spacing that may be shorter than the target depth. Also, at early times, for a certain ratio of the dipole separation to the target depth, there is a dramatic increase in the resolution of the response. Thus, it is possible to resolve suppressed layers of an A‐type section in this type of sounding. A study of the effects of transmitter ramp time and receiver bandwidth on the transient apparent resistivity curves shows that a very fast current shut‐off and wideband measurement are required to realize all the possibilities suggested by this modeling. Some 3-D transient electromagnetic (TEM) modeling was also done to simulate (1) a lateral variation in the resistivity of the middle layer of an A‐type section and (2) a weak zone of limited horizontal extent in the substratum of a two‐layer section. We observed that the 3-D inclusion has less effect at late time but is more pronounced at early time. In view of the above results, we conclude that the transient E‐field sounding with a grounded wire source can be used in place of a conventional DC resistivity sounding to overcome the problem of poor resolution due to the suppression of the intermediate layer in a geoelectric section where the resistivity increases with depth. As such, it has a potential application in groundwater as well as geotechnical surveys, because together with the overlying weathered layer, the fractured rock constitutes the aquifer in hard rocks.

De-noising of transient electromagnetic data based on the long short-term memory-autoencoder

2020 ◽  
Vol 224 (1) ◽  
pp. 669-681
Author(s):  
Sihong Wu ◽  
Qinghua Huang ◽  
Li Zhao
Keyword(s):  
Field Data ◽  
Short Term Memory ◽  
Noise Removal ◽  
Data Sets ◽  
Late Time ◽  
Short Term ◽  
Term Memory ◽  
Transient Electromagnetic ◽  
Long Short Term Memory

SUMMARY Late-time transient electromagnetic (TEM) data contain deep subsurface information and are important for resolving deeper electrical structures. However, due to their relatively small signal amplitudes, TEM responses later in time are often dominated by ambient noises. Therefore, noise removal is critical to the application of TEM data in imaging electrical structures at depth. De-noising techniques for TEM data have been developed rapidly in recent years. Although strong efforts have been made to improving the quality of the TEM responses, it is still a challenge to effectively extract the signals due to unpredictable and irregular noises. In this study, we develop a new type of neural network architecture by combining the long short-term memory (LSTM) network with the autoencoder structure to suppress noise in TEM signals. The resulting LSTM-autoencoders yield excellent performance on synthetic data sets including horizontal components of the electric field and vertical component of the magnetic field generated by different sources such as dipole, loop and grounded line sources. The relative errors between the de-noised data sets and the corresponding noise-free transients are below 1% for most of the sampling points. Notable improvement in the resistivity structure inversion result is achieved using the TEM data de-noised by the LSTM-autoencoder in comparison with several widely-used neural networks, especially for later-arriving signals that are important for constraining deeper structures. We demonstrate the effectiveness and general applicability of the LSTM-autoencoder by de-noising experiments using synthetic 1-D and 3-D TEM signals as well as field data sets. The field data from a fixed loop survey using multiple receivers are greatly improved after de-noising by the LSTM-autoencoder, resulting in more consistent inversion models with significantly increased exploration depth. The LSTM-autoencoder is capable of enhancing the quality of the TEM signals at later times, which enables us to better resolve deeper electrical structures.

The Application of TEM on Detecting Mine Goaf

2014 ◽  
Vol 1073-1076 ◽  
pp. 2153-2157
Author(s):  
Yong Jun Li ◽  
Xiao Ming Li ◽  
Ting Chen
Keyword(s):  
Water Content ◽  
Apparent Resistivity ◽  
Electromagnetic Method ◽  
Transient Electromagnetic Method ◽  
Electrical Characteristics ◽  
Geophysical Prospecting ◽  
Secondary Field ◽  
Low Resistivity ◽  
Transient Electromagnetic

Transient electromagnetic method is one of the geophysical prospecting methods to detect mine goaf. The paper analyzes the unique electrical characteristics of the stratum containing goaf. TEM inverts the apparent resistivity and delineates the mine goaf and determines water content by observing the pure secondary field. The method is sensitive to geologic bodies of low resistivity and has higher resolution. The paper takes some one mine in Shanxi as example to prove the practicability and effectiveness of TEM in production. It has certain reference significance in detecting mine goaf.

scholarly journals Diffusion Law of Whole-Space Transient Electromagnetic Field Generated by the Underground Magnetic Source and Its Application

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 63415-63425 ◽  
Author(s):  
Jianghao Chang ◽  
Jingcun Yu ◽  
Juanjuan Li ◽  
Guoqiang Xue ◽  
Reza Malekian ◽  
...  
Keyword(s):  
Electromagnetic Field ◽  
Transient Electromagnetic ◽  
Magnetic Source ◽  
Whole Space

Resistivity-depth imaging of airborne transient electromagnetic method based on an artificial neural network

2020 ◽  
Author(s):  
Jifeng Zhang ◽  
Bing Feng ◽  
Dong Li
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Bp Neural Network ◽  
Apparent Resistivity ◽  
Electromagnetic Method ◽  
Electromagnetic Response ◽  
Model Parameters ◽  
Transient Electromagnetic Method ◽  
Transient Electromagnetic ◽  
Artificial Neural

<p>An artificial neural network, which is an important part of artificial intelligence, has been widely used to many fields such as information processing, automation and economy, and geophysical data processing as one of the efficient tools. However, the application in geophysical electromagnetic method is still relatively few. In this paper, BP neural network was combined with airborne transient electromagnetic method for imaging subsurface geological structures.</p><p>We developed an artificial neural network code to map the distribution of geologic conductivity in the subsurface for the airborne transient electromagnetic method. It avoids complex derivation of electromagnetic field formula and only requires input and transfer functions to obtain the quasi-resistivity image section. First, training sample set, which is airborne transient electromagnetic response of homogeneous half-space models with the different resistivity, is formed and network model parameters include the flight altitude and the time constant, which were taken as input variables of the network, and pseudo-resistivity are taken as output variables. Then, a double hidden layer BP neural network is established in accordance with the mapping relationship between quasi-resistivity and airborne transient electromagnetic response. By analyzing mean square error curve, the training termination criterion of BP neural network is presented. Next, the trained BP neural network is used to interpret the airborne transient electromagnetic responses of various typical layered geo-electric models, and it is compared with those of the all-time apparent resistivity algorithm. After a lot of tests, reasonable BP neural network parameters were selected, and the mapping from airborne TEM quasi-resistivity was realized. The results show that the resistivity imaging from BP neural network approach is much closer to the true resistivity of model, and the response to anomalous bodies is better than that of all-time apparent resistivity numerical method. Finally, this imaging technique was use to process the field data acquired by the airborne transient method from Huayangchuan area. Quasi-resistivity depth section calculated by BP neural network and all-time apparent resistivity is in good agreement with the actual geological situation, which further verifies the effectiveness and practicability of this algorithm.</p>

SALT BED IDENTIFICATION FROM UNFOCUSED RESISTIVITY LOGS

Geophysics ◽  
1961 ◽  
Vol 26 (3) ◽  
pp. 320-341
Author(s):  
J. R. Lishman
Keyword(s):  
Electrical Resistivity ◽  
Apparent Resistivity ◽  
Borehole Diameter ◽  
Drilling Fluids ◽  
Characteristic Shape ◽  
Resistivity Logs

Salt beds have almost infinite electrical resistivity. They differ from other infinitely resistive beds in that they are usually soluble in drilling fluids, and give rise to enlarged boreholes. An infinitely resistive bed lying between shales may be recognized from the characteristic shape of the electric log resistivity curves, and the ratios of their readings. Any one of the curves may then be used to compute the borehole diameter, and hence decide whether the bed is salt. Where a washed out salt bed is adjacent to another infinitely resistive bed in which the borehole is to gauge, the configuration of the curves is very characteristic. Apparent resistivity ratios again help to identify the salt.

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