A spatially constrained 1D inversion algorithm for quasi-3D conductivity imaging: Application to DUALEM-421 data collected in a riverine plain

Geophysics ◽  
2011 ◽  
Vol 76 (2) ◽  
pp. B43-B53 ◽  
Author(s):  
Fernando Acácio Monteiro Santos ◽  
John Triantafilis ◽  
Kira Bruzgulis
Keyword(s):  
Electromagnetic Induction ◽  
Clay Content ◽  
Agricultural Systems ◽  
Stream Channel ◽  
Inversion Algorithm ◽  
Vertical Extent ◽  
Murray Darling Basin ◽  
Imaging Application ◽  
Em Induction ◽  
Conductivity Imaging

The efficient use of water in irrigated agricultural systems is of increasing importance given the changes in climatic patterns currently being experienced in the irrigated areas of the Murray-Darling Basin (MDB) in Australia. In previous research, electromagnetic (EM) induction instruments have been used to map the distribution of the clay content in those areas. However, describing their vertical extent and connectivity with groundwater tables or stratigraphic features such as paleochannels has not been studied adequately. One of the reasons for the paucity of research is the lack of suitable instrumentation or software to invert apparent conductivity (σa) data. The aim of this research is to demonstrate how DUALEM-421 equipment, which operates using electromagnetic induction theory, can be used to map not only the areal distribution of a prior stream channel but its vertical extent by inputting the data into a 1D spatially constrained algorithm for quasi-3D conductivity imaging. We discovered how the inversion of the apparent electrical conductivity, measured in the horizontal (HCP) and perpendicular (PRP) arrays, characterizes the Quaternary alluvial clays which dominate the riverine plain of the lower Gwydir valley, and indicates the location and extent of a prior stream channel and its sediments across Auscott Midkin field 11. We found the calculated conductivity values favorably represent the known stratigraphy of these physiographic units. Our results suggest the prior stream channel may be interconnected with a more extensive paleochannel.

2-Dimensional soil and vadose-zone representation using an EM38 and EM34 and a laterally constrained inversion model

Soil Research ◽  
2009 ◽  
Vol 47 (8) ◽  
pp. 809 ◽  
Author(s):  
J. Triantafilis ◽  
F. A. Monteiro Santos
Keyword(s):  
Electrical Conductivity ◽  
Vadose Zone ◽  
Root Zone ◽  
Clay Content ◽  
Inversion Algorithm ◽  
Near Surface ◽  
Particle Size Fractions ◽  
Murray Darling Basin ◽  
Full Solution ◽  
Soil Particle Size Fractions

The network of prior streams and palaeochannels common across the Riverine Plains of the Murray–Darling Basin act as conduits for the redistribution of water and soluble salts beneath the root-zone. To improve scientific understanding of these hydrological processes there is the need to better represent and map the connectivity and spatial extent of these physiographic and stratigraphic features. Groundbased electromagnetic (EM) instruments, which measure bulk soil electrical conductivity (σa), have been used widely to map their areal distribution across the landscape. However, methods to resolve their location with depth have rarely been attempted. In this paper we employ a 1-D inversion algorithm with 2-D smoothness constraints to predict the true electrical conductivity (σ) at discrete depth increments using EM data. The EM data we use include the root-zone measuring EM38 and the deeper sensing EM34. We collected EM38 data in the vertical (EM38v) and horizontal (EM38h) dipole modes and EM34 data in the horizontal mode and coil spacing of 10, 20, and 40 m (respectively, EM34-10, EM34-20, and EM34-40). In order to compare and contrast the value of the various EM data we carried out multiple inversions using different combinations, which include: independent inversions of (i) EM38 (root-zone) and (ii) EM34 data (vadose-zone), and in combination using (iii) EM38v, EM38h, and EM34-10 (near-surface), and (iv) all 5 EM datasets (regolith) available. The general patterns of σ are shown to compare favourably with the known pedoderms, physiographic, and stratigraphic features and soil particle size fractions collected from calibration cores drilled across the lower Macquarie Valley study area. In general we find that the EM38 assists in resolving root-zone variability, specifically duplex soil profiles and physiographic features such as prior streams, while the use of the EM34 assists in resolving the stratigraphic nature of the vadose-zone and specifically the likely location of palaeochannels and subsurface anomalies that may indicate the location of good quality groundwater and/or clay aquitards. In this case, our potential to use σ to predict clay content is limited by the non-linearity of the cumulative functions. In order to improve on the non-linearity of our inversion we need to develop a full solution of the forward problem.

Petrophysical inversion of borehole array-induction logs: Part II — Field data examples

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. G261-G268 ◽  
Author(s):  
Carlos Torres-Verdín ◽  
Faruk O. Alpak ◽  
Tarek M. Habashy
Keyword(s):  
Electromagnetic Induction ◽  
Layer By Layer ◽  
Laboratory Measurements ◽  
Inversion Algorithm ◽  
Vertical Wells ◽  
Gas Field ◽  
Rock Formations ◽  
Resistivity Logs ◽  
Porosity And Permeability ◽  
Induction Logs

We describe the application of Alpak et al.’s (2006) petrophysical inversion algorithm to the interpretation of borehole array induction logs acquired in an active North American gas field. Layer-by-layer values of porosity and permeability were estimated in two closely spaced vertical wells that penetrated the same horizontal rock formation. The wells were drilled with different muds and overbalance pressures, and the corresponding electromagnetic induction logs were acquired with different tools. Rock-core laboratory measurements available in one of the two wells were used to constrain the efficiency of gas displacement by water-based mud during the process of invasion. Estimated values of porosity and permeability agree well with measurements performed on rock-core samples. In addition to estimating porosity and permeability, the petrophysical inversion algorithm provided accurate spatial distributions of gas saturation in the invaded rock formations that were not possible to obtain with conventional procedures based solely on the use of density and resistivity logs.

Determination of relative angles and anisotropic resistivity using multicomponent induction logging data

Geophysics ◽  
2004 ◽  
Vol 69 (4) ◽  
pp. 898-908 ◽  
Author(s):  
Zhiyi Zhang ◽  
Liming Yu ◽  
Berthold Kriegshäuser ◽  
Lev Tabarovsky
Keyword(s):  
Sensitivity Analysis ◽  
Azimuth Angle ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Data Set ◽  
Simultaneous Inversion ◽  
Induction Logging ◽  
Em Induction ◽  
Whole Space ◽  
Dip Angle

We have developed a new algorithm that retrieves information about relative dip angle, relative azimuth angle, vertical resistivity, and horizontal resistivity from multicomponent EM induction logging data. To investigate how relative dip and azimuth angles affect multicomponent induction logging data, we performed a sensitivity analysis using an anisotropic whole space model. Based upon the sensitivity analysis, we designed a two‐step procedure to recover relative dip, relative azimuth, horizontal resistivity, and vertical resistivity. In the first step, the observed data are transformed into a new data set independent of the azimuth angle; a simultaneous inversion method recovers relative dip angle, vertical resistivity, and horizontal resistivity. In the second step, a 1D line search is performed to decide relative azimuth angle. Synthetic and field data tests indicate that the new inversion algorithm can extract information about relative dip and azimuth angles as well as the anisotropic resistivity structure from multicomponent induction loggingdata.

Mapping Clay Content across Boundaries at the Landscape Scale with Electromagnetic Induction

2007 ◽  
Vol 71 (6) ◽  
pp. 1740-1747 ◽  
Author(s):  
U. Weller ◽  
M. Zipprich ◽  
M. Sommer ◽  
W. Zu Castell ◽  
M. Wehrhan
Keyword(s):  
Electromagnetic Induction ◽  
Clay Content ◽  
Landscape Scale

scholarly journals Three-Dimensional Mapping of Clay and Cation Exchange Capacity of Sandy and Infertile Soil Using EM38 and Inversion Software

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3936 ◽  
Author(s):  
Tibet Khongnawang ◽  
Ehsan Zare ◽  
Dongxue Zhao ◽  
Pranee Srihabun ◽  
John Triantafilis
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Cation Exchange ◽  
Cation Exchange Capacity ◽  
Three Dimensional ◽  
Exchange Capacity ◽  
Inversion Algorithm ◽  
Three Dimensional Mapping ◽  
Em Induction ◽  
Leave One Out

Most cultivated upland areas of northeast Thailand are characterized by sandy and infertile soils, which are difficult to improve agriculturally. Information about the clay (%) and cation exchange capacity (CEC—cmol(+)/kg) are required. Because it is expensive to analyse these soil properties, electromagnetic (EM) induction instruments are increasingly being used. This is because the measured apparent soil electrical conductivity (ECa—mS/m), can often be correlated directly with measured topsoil (0–0.3 m), subsurface (0.3–0.6 m) and subsoil (0.6–0.9 m) clay and CEC. In this study, we explore the potential to use this approach and considering a linear regression (LR) between EM38 acquired ECa in horizontal (ECah) and vertical (ECav) modes of operation and the soil properties at each of these depths. We compare this approach with a universal LR relationship developed between calculated true electrical conductivity (σ—mS/m) and laboratory measured clay and CEC at various depths. We estimate σ by inverting ECah and ECav data, using a quasi-3D inversion algorithm (EM4Soil). The best LR between ECa and soil properties was between ECah and subsoil clay (R2 = 0.43) and subsoil CEC (R2 = 0.56). We concluded these LR were unsatisfactory to predict clay or CEC at any of the three depths, however. In comparison, we found that a universal LR could be established between σ with clay (R2 = 0.65) and CEC (R2 = 0.68). The LR model validation was tested using a leave-one-out-cross-validation. The results indicated that the universal LR between σ and clay at any depth was precise (RMSE = 2.17), unbiased (ME = 0.27) with good concordance (Lin’s = 0.78). Similarly, satisfactory results were obtained by the LR between σ and CEC (Lin’s = 0.80). We conclude that in a field where a direct LR relationship between clay or CEC and ECa cannot be established, can still potentially be mapped by developing a LR between estimates of σ with clay or CEC if they all vary with depth.

scholarly journals Electromagnetic induction in a fully 3‐D anisotropic earth

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1104-1114 ◽  
Author(s):  
Chester J. Weiss ◽  
Gregory A. Newman
Keyword(s):  
Finite Difference ◽  
Electromagnetic Induction ◽  
Water Saturation ◽  
Research Problem ◽  
Analytic Solutions ◽  
Electrical Anisotropy ◽  
Staggered Grid ◽  
Ongoing Research ◽  
Em Induction ◽  
D Model

The bulk electrical anisotropy of sedimentary formations is a macroscopic phenomenon which can result from the presence of porosity variations, laminated shaly sands, and water saturation. Accounting for its effect on induction log responses is an ongoing research problem for the well‐logging community since these types of sedimentary structures have long been correlated with productive hydrocarbon reservoirs such as the Jurassic Norphlet Sandstone and Permian Rotliegendes Sandstone. Presented here is a staggered‐grid finite‐difference method for simulating electromagnetic (EM) induction in a fully 3‐D anisotropic medium. The electrical conductivity of the formation is represented as a full 3 × 3 tensor whose elements can vary arbitrarily with position throughout the formation. To demonstrate the validity of this approach, finite‐difference results are compared against analytic and quasi‐analytic solutions for tractable 1‐D and 3‐D model geometries. As a final example, we simulate 2C–40 induction tool responses in a crossbedded aeolian sandstone to illustrate the magnitude of the challenge faced by interpreters when electrical anisotropy is neglected.

scholarly journals Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

2017 ◽  
Vol 21 (1) ◽  
pp. 495-513 ◽  
Author(s):  
Edoardo Martini ◽  
Ulrike Werban ◽  
Steffen Zacharias ◽  
Marco Pohle ◽  
Peter Dietrich ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Soil Moisture ◽  
Spatial Pattern ◽  
Soil Properties ◽  
Electromagnetic Induction ◽  
Scale Validation ◽  
Low Cost ◽  
Monitoring Network ◽  
Clay Content ◽  
Temporal Variations

Abstract. Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa–θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.

scholarly journals Understanding Fields by Remote Sensing: Soil Zoning and Property Mapping

2020 ◽  
Vol 12 (7) ◽  
pp. 1116 ◽  
Author(s):  
Onur Yuzugullu ◽  
Frank Lorenz ◽  
Peter Fröhlich ◽  
Frank Liebisch
Keyword(s):  
Soil Properties ◽  
Precision Agriculture ◽  
Soil Property ◽  
Clay Content ◽  
Agricultural Systems ◽  
Property Prediction ◽  
High Agreement ◽  
New Era ◽  
Field Management ◽  
Agronomic Yield

Precision agriculture aims to optimize field management to increase agronomic yield, reduce environmental impact, and potentially foster soil carbon sequestration. In 2015, the Copernicus mission, with Sentinel-1 and -2, opened a new era by providing freely available high spatial and temporal resolution satellite data. Since then, many studies have been conducted to understand, monitor and improve agricultural systems. This paper presents results from the SolumScire project, focusing on the prediction of the spatial distribution of soil zones and topsoil properties, such as pH, soil organic matter (SOM) and clay content in agricultural fields through random forest algorithms. For this purpose, samples from 120 fields were investigated. The zoning and soil property prediction has an accuracy greater than 90%. This is supported by a high agreement of the derived zones with farmer’s observations. The trained models revealed a prediction accuracy of 94%, 89% and 96% for pH, SOM and clay content, respectively. The obtained models for soil properties can support precision field management, the improvement of soil sampling and fertilization strategies, and eventually the management of soil properties such as SOM.

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