Enhanced Interpretation of Russian and Old Electrical Resistivity Logs Using Modeling and Inversion Methods

1997 ◽  
Author(s):  
M.A. Frenkel ◽  
A.G. Mezzatesta ◽  
K.-M. Strack
Keyword(s):  
Electrical Resistivity ◽  
Inversion Methods ◽  
Resistivity Logs ◽  
And Inversion

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.

scholarly journals A review of open software resources in python for electrical resistivity modelling

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Yonatan Garkebo Doyoro ◽  
Ping-Yu Chang ◽  
Jordi Mahardika Puntu ◽  
Ding-Jiun Lin ◽  
Tran Van Huu ◽  
...  
Keyword(s):  
Electrical Resistivity ◽  
Electrical Resistivity Tomography ◽  
Geophysical Research ◽  
Resistivity Tomography ◽  
Subsurface Structures ◽  
Data Inversion ◽  
Scripting Language ◽  
And Inversion ◽  
Geoelectric Data ◽  
Insight Into

AbstractGeophysical modelling performs to obtain subsurface structures in agreement with measured data. Freeware algorithms for geoelectrical data inversion have not been widely used in geophysical communities; however, different open-source modelling/inversion algorithms were developed in recent years. In this study, we review the structures and applications of openly Python-based inversion packages, such as pyGIMLi (Python Library for Inversion and Modelling in Geophysics), BERT (Boundless Electrical Resistivity Tomography), ResIPy (Resistivity and Induced Polarization with Python), pyres (Python wrapper for electrical resistivity modelling), and SimPEG (Simulation and Parameter Estimation in Geophysics). In addition, we examine the recovering ability of pyGIMLi, BERT, ResIPy, and SimPEG freeware through inversion of the same synthetic model forward responses. A versatile pyGIMLi freeware is highly suitable for various geophysical data inversion. The SimPEG framework is developed to allow the user to explore, experiment with, and iterate over multiple approaches to the inverse problem. In contrast, BERT, pyres, and ResIPy are exclusively designed for geoelectric data inversion. BERT and pyGIMLi codes can be easily modified for the intended applications. Both pyres and ResIPy use the same mesh designs and inversion algorithms, but pyres uses scripting language, while ResIPy uses a graphical user interface (GUI) that removes the need for text inputs. Our numerical modelling shows that all the tested inversion freeware could be effective for relatively larger targets. pyGIMLi and BERT could also obtain reasonable model resolutions and anomaly accuracies for small-sized subsurface structures. Based on the heterogeneous layered model and experimental target scenario results, the geoelectrical data inversion could be more effective in pyGIMLi, BERT, and SimPEG freeware packages. Moreover, this study can provide insight into implementing suitable inversion freeware for reproducible geophysical research, mainly for geoelectrical modelling.

scholarly journals How Do Secondary Minerals in Granite Help Distinguish Paleo- from Present-Day Permeable Fracture Zones? Joint Interpretation of SWIR Spectroscopy and Geophysical Logs in the Geothermal Wells of Northern Alsace

Geofluids ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Carole Glaas ◽  
Jeanne Vidal ◽  
Patricia Patrier ◽  
Jean-François Girard ◽  
Daniel Beaufort ◽  
...  
Keyword(s):  
Electrical Resistivity ◽  
Absorption Band ◽  
Hydrothermal Alteration ◽  
Granitic Rocks ◽  
Upper Rhine Graben ◽  
Fracture Zones ◽  
Band Area ◽  
Resistivity Logs ◽  
Geothermal Wells ◽  
Geophysical Logs

The investigation of permeable hydrothermally altered and fractured zones and their distribution is a key issue for the understanding of fluid circulation in granitic rocks, on which the success of geothermal projects relies. Based on the use of short-wave infrared (SWIR) spectroscopy applied to rock cuttings coupled with interpretation of geophysical logs, we propose an investigation of the clay signature of fault and fracture zones (FZ) inside the granitic basement. This methodology was applied to two geothermal wells: GRT-2 from the Rittershoffen and GPK-1 from the Soultz-sous-Forêts (Soultz) geothermal sites, both located in the Upper Rhine Graben (URG). A total of 1430 SWIR spectra were acquired and analysed. Variations in the 2200 nm absorption band area are correlated with hydrothermal alteration grades. The 2200 nm absorption band area is found to reflect the illite quantity and its variations in the granitic basement. Low, stable values are observed in the unaltered granite facies, showing good reproducibility of the method, whereas scattered high values are associated with high hydrothermal alteration and FZs. Variations in the 2200 nm absorption band area were correlated with the gamma ray and electrical resistivity logs. This procedure allowed us to confirm that illite mainly controls the resistivity response except inside the permeable FZs, where the resistivity response is controlled by the geothermal brine. Thus, the architecture of these permeable FZs was described precisely by using a combination of the 2200 nm absorption band area data and the electrical resistivity log. Moreover, by correlation with other geophysical logs (temperature (T), porosity, and density), paleo-permeable and currently permeable FZs inside the reservoir were distinguished. The correlation of SWIR spectroscopy with electrical resistivity logs appears to be a robust tool for geothermal exploration in granitic reservoirs in the URG.

Electrically Inferred Subsurface Fractures in the Crystalline Hard Rocks of an Experimental Hydrogeological Park, Southern India

Geophysics ◽  
2021 ◽  
pp. 1-43
Author(s):  
Ved Prakash Maurya ◽  
Subash Chandra ◽  
Sahebrao Sonkamble ◽  
K. Lohith Kumar ◽  
ERUGU NAGAIAH ◽  
...  
Keyword(s):  
Electrical Resistivity ◽  
Apparent Resistivity ◽  
Time Lapse ◽  
Granitic Rocks ◽  
Aquifer Recharge ◽  
Flow Paths ◽  
Resistivity Model ◽  
Subsurface Fractures ◽  
Water Saturated ◽  
And Inversion

We investigated a network of fractures forming the flow paths within the crystalline granitic rocks of an experimental hydrogeological park (EHP) with the help of electrical resistivity surveys. The experimental study located at managed aquifer recharge (MAR) site of EHP has measured a distinct variation in the apparent resistivity for deeper electrical signals that localize the presence of interconnected water-saturated fractures. Usually, profiles close to the MAR tank depict low apparent resistivity values from deep signals across in-situ fractures and resistivity amplitude increases away from the tank. We modeled and simulated the presence of water-saturated fractures by a simple three-layered model having embedded shallow heterogeneities in the saprolite layer, vertically interconnected multiple thin conductive horizontal layers in the fissured zone, and an underlain un-weathered crystalline granitic basement. These fractures produce a distinct variation in the resistivity both for modeling and inversion exercises. The decadal time-lapse electrical resistivity surveys, after the establishment of the MAR tank, mark similar repetitive main features with a distinct drop in resistivity depicting the presence of water-saturated fractures. An overview of 3D resistivity model characterizes the subsurface heterogeneities, presence of possible flow paths for shallow depths <30 m, and indicative of possible flows in the interconnected deep fractures for depths >30m.

scholarly journals Testing alternative uses of electromagnetic data to reduce the prediction error of groundwater models

2016 ◽  
Vol 20 (5) ◽  
pp. 1925-1946 ◽  
Author(s):  
Nikolaj Kruse Christensen ◽  
Steen Christensen ◽  
Ty Paul A. Ferre
Keyword(s):  
Electrical Resistivity ◽  
Hydraulic Conductivity ◽  
Prediction Error ◽  
Model Calibration ◽  
Hydrologic Model ◽  
Geophysical Data ◽  
Model Parameters ◽  
Calibration Data ◽  
Groundwater Model ◽  
And Inversion

Abstract. In spite of geophysics being used increasingly, it is often unclear how and when the integration of geophysical data and models can best improve the construction and predictive capability of groundwater models. This paper uses a newly developed HYdrogeophysical TEst-Bench (HYTEB) that is a collection of geological, groundwater and geophysical modeling and inversion software to demonstrate alternative uses of electromagnetic (EM) data for groundwater modeling in a hydrogeological environment consisting of various types of glacial deposits with typical hydraulic conductivities and electrical resistivities covering impermeable bedrock with low resistivity (clay). The synthetic 3-D reference system is designed so that there is a perfect relationship between hydraulic conductivity and electrical resistivity. For this system it is investigated to what extent groundwater model calibration and, often more importantly, model predictions can be improved by including in the calibration process electrical resistivity estimates obtained from TEM data. In all calibration cases, the hydraulic conductivity field is highly parameterized and the estimation is stabilized by (in most cases) geophysics-based regularization. For the studied system and inversion approaches it is found that resistivities estimated by sequential hydrogeophysical inversion (SHI) or joint hydrogeophysical inversion (JHI) should be used with caution as estimators of hydraulic conductivity or as regularization means for subsequent hydrological inversion. The limited groundwater model improvement obtained by using the geophysical data probably mainly arises from the way these data are used here: the alternative inversion approaches propagate geophysical estimation errors into the hydrologic model parameters. It was expected that JHI would compensate for this, but the hydrologic data were apparently insufficient to secure such compensation. With respect to reducing model prediction error, it depends on the type of prediction whether it has value to include geophysics in a joint or sequential hydrogeophysical model calibration. It is found that all calibrated models are good predictors of hydraulic head. When the stress situation is changed from that of the hydrologic calibration data, then all models make biased predictions of head change. All calibrated models turn out to be very poor predictors of the pumping well's recharge area and groundwater age. The reason for this is that distributed recharge is parameterized as depending on estimated hydraulic conductivity of the upper model layer, which tends to be underestimated. Another important insight from our analysis is thus that either recharge should be parameterized and estimated in a different way, or other types of data should be added to better constrain the recharge estimates.

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