A discussion of 2D induced polarization effects in airborne electromagnetic and inversion with a robust 1D laterally constrained inversion scheme
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Recently, the interest in the induced polarization (IP) phenomenon in airborne time-domain electromagnetic (ATEM) data has increased considerably. IP may affect the ATEM data significantly and mask underlying geologic structures. To simulate 2D airborne IP data, a 2D finite-element forward-modeling algorithm has been developed with the dispersive conductivity described by the well-known Cole-Cole model. We verify our algorithm by comparison with the 1D solution of the AarhusInv code. Two-dimensional forward responses on six synthetic models, mimicking archetypal 2D conductive and chargeable anomalies, have been generated, and the results indicate that 2D IP affects the data significantly. Differences between the 2D IP responses and the 1D IP responses are evident above the 2D anomalies and at their edges. These differences are similar to what is found when comparing 2D and 1D forward responses over conductive 2D anomalies without considering IP. We evaluate an effective robust inversion scheme to recover the 2D IP parameters using the 1D laterally constrained inversion (LCI) scheme. The inversion of the synthetic data using the robust scheme indicates that not only can the IP parameters be recovered, but also the IP inversions can provide more accurate resistivity sections than a resistivity-only inversion, in terms of resistivity values and anomaly thickness/depth. The field example from Hope Bay area in Canada is even more valuable, considering that part of the profile consists of only negative data, which cannot be inverted with a resistivity-only scheme. Furthermore, the edge effects at the anomaly boundaries are less pronounced in the IP parameters than in the resistivity parameter on the synthetic models with more conductive backgrounds.Keywords:
Induced polarization
Synthetic data
Semi-airborne transient electromagnetic (SATEM) method has been efficiently used recently in geophysical exploration due to its relatively portability compared to the standard airborne surveys. However, the SATEM data are often complicated by induced polarization (IP) effects manifesting as abnormal decay and sign reversal in the responses. The IP information can be extracted from SATEM data by joint inversion of the electromagnetic data into the electrical resistivity and IP parameters described in Cole-Cole model. In this paper, we introduce a quasi-two-dimensional inversion scheme to recover the resistivity and IP parameters from SATEM responses by (1) a fast semi-analytical method for Jacobian matrix calculation; and (2) a staged inversion strategy with lateral constraints. The methodology is examined on two synthetic polarized models. Our study indicates that the proposed scheme can improve inversion stability and recover the underground resistivity and IP property distributions.
Induced polarization
Software portability
Magnetotellurics
Synthetic data
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The paper presents a short overview about the application of joint inversion in geophysics. It gives also an alternative explanation for the term of "different data sets" and discusses what types of inversion procedures can be considered as joint inversion. Nowadays there are no standard standpoints using the appellation joint inversion. What is joint inversion? Based on the information matrix an answer could be given for this question what could be regarded as various types of data sets that are inverted simultaneously. We would like to expand the explanation—that is professed by many researchers—of the method that regards only the simultaneous inversion of data sets based on different physical parameters as joint inversion.
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Synthetic data
Magnetotellurics
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Prestack simultaneous inversion was performed on synthetic and measured seismic data to appraise the influence of several factors to estimation of P- and S-wave velocity and especially density. The measured data from Western Siberia were used to generate the synthetic data. Analysis on synthetic data indicates that even in the ideal case of noise-free data we have to carry on about angle range. For accurate density estimation it is necessary to use far-angle data (more than 30 degree). Lastly 5-50% random noise was added to the synthetic data, and misfits between inversion results and model data were analyzed. Finally inversion was performed on measured data. Based on results of inversion sandstones with good reservoir quality were detected
Prestack
Synthetic data
Inverse transform sampling
Data Processing
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We have developed a synthetic multiparametric modeling and inversion exercise undertaken to study the robustness of inverting airborne time-domain electromagnetic (TDEM) data to extract Cole-Cole parameters. The following issues were addressed: nonuniqueness, ill posedness, dependency on manual processing and the effect of constraints, and a priori information. We have used a 1D layered earth model approximation and lateral constraints. Synthetic simulations were performed for several models and the corresponding Cole-Cole parameters. The possibility to recover these models by means of laterally constrained multiparametric inversion was evaluated, including recovery of chargeability distributions from shallow and deep targets based on analysis of induced polarization (IP) effects, simulated in airborne TDEM data. Different scenarios were studied, including chargeable targets associated with the conductive and resistive environments. In particular, four generic models were considered for the exercise: a sulfide model, a kimberlite model, and two generic models focusing on the depth of investigation. Our study indicated that, in cases when relaxation time ([Formula: see text]) values are in the range to which the airborne electromagnetic is most sensitive (e.g., approximately 1 ms), it is possible to recover deep chargeable targets (to depths more than 130 m) in association with high electrical conductivity and in resistive environments. Furthermore, it was found that the recovery of a deep conductor, masked by a shallower chargeable target, became possible only when full Cole-Cole modeling was used in the inversion. Lateral constraints improved the recoverability of model parameters. Finally, modeling IP effects increased the accuracy of recovered electrical resistivity models.
Resistive touchscreen
Synthetic data
Induced polarization
Robustness
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An innovative inversion code, named “Curupira v1.0”, has been developed using Matlab to determine the vertical distribution of resistivity beneath the subsoil. The program integrates Vertical Electrical Sounding (VES), successful in shallow subsurface exploration and Time Domain Electromagnetic (TEM) techniques, better suited for deeper exploration, both of which are widely employed in geophysical exploration. These methodologies involve calculating subsurface resistivity through appropriate inversion processes. To address the ill-posed nature of inverse problems in geophysics, a joint inversion scheme combining VES and TEM data has been incorporated into Curupira v1.0. The software has been tested on both synthetic and real-world data, the latter of which was acquired from the Parana sedimentary basin which we summarise here. The results indicate that the joint inversion of VES and TEM techniques offers improved recovery of simulated models and demonstrates significant potential for hydrogeological studies.
Vertical electrical sounding
Induced polarization
Subsoil
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Time-lapse seismic data contains information about changes in the subsurface, and are nowadays used as an effective tool to characterize changes in reservoirs due to production of oil and gas or injection of CO2. The full waveform inversion (FWI) method can be used to detect these changes. Three different approaches for time-lapse FWI are presented: (1) performing independent inversion for each dataset, and then compare the inversion results; (2) first invert for one of the datasets and then use the end model from the first inversion as initial model for the inversion for the other datasets; (3) similar to (2), but the data consists of a combination of the optimal data of previous inversion and the difference between the observed datasets. The three approaches are applied on synthetic and real timelapse marine streamer seismic data. The approaches are able to detect and describe the changes in velocities in the subsurface.
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