Search Results (4)

The paper considers one of the possible statements of inverse problems in gravimetric and magnetometric remote sensing, proposes a new approach to its solution and formulates algorithms that implement this approach. The problem under consideration consists of finding hypothetical sources of the corresponding potential fields at a given depth based on these fields measured on the Earth’s surface. The problem is reduced to solving systems of linear algebraic equations (SLAE) with ill-conditioned matrices. The proposed approach to the numerical solution is based on improving the condition number of the SLAE’s matrix. A numerical algorithm implementing the proposed approach that is applicable to the stable solution of degenerate and ill-conditioned SLAEs with an approximately given right-hand side is formulated in general form. The algorithm uses the SVD decomposition of the SLAE’s matrix and constructs a new matrix close to the original one with a better (smaller) condition number. An approximate solution to the original SLAE is calculated using the pseudoinverse of the new matrix. The results of a theoretical study of the algorithm are presented and the main properties of the new matrix are given. In particular, the reduction of its condition number is estimated. Several implementations of this algorithm are considered, in particular, the MPMI method, which is based on the use of so-called minimal pseudoinverse matrices. For the model problem, the advantage of the MPMI method over a number of other common methods is shown. The MPMI method is applied to solve the considered problems of gravity exploration and magnetic exploration both in the separate solution of these inverse problems and in their joint solution when processing geophysical data for the Kathu region, in the Northern Cape area of South Africa. Full article

In this article, the authors developed a novel method for the moisture mapping of the soil surface of agrophytocenosis using a neural network based on synchronized radar and multispectral optoelectronic data from Sentinel-1,2. The significance of this research lies in its potential to enhance precision farming practices, which are increasingly vital in addressing global agricultural challenges such as water scarcity and the need for sustainable resource management. To verify the developed method, data from two experimental plots were utilized. These plots were located on irrigated soybean crops, with the first plot situated on the right bank (plot No. 1) and the second on the left bank (plot No. 2) of the lower Volga River. Two experimental soil moisture geodatasets were created through measurements and geo-referencing points using the gravimetric method (for plot No. 1) and the proximal sensing method (for plot No. 2) employing the Soil Moisture Sensor ML3-KIT (THETAKIT, Delta). The soil moisture retrieval algorithm was based on the use of a neural network to predict the reflection coefficient of an electro-magnetic wave from the soil surface, followed by inversion into soil moisture using a dielectric model that takes into account the soil texture. The input parameter of the neural network was the ratio of the microwave radar vegetation index (calculated based on Sentinel-1 data) to the index (calculated based on the data of multispectral optoelectronic channels 8 and 11 of Sentinel-2). The retrieved soil moisture values were compared with in situ measurements, showing a determination coefficient of 0.44–0.65 and a standard deviation of 2.4–4.2% for plot No. 1 and similar metrics for plot No. 2. The conducted research laid the groundwork for developing a new technology for remote sensing of soil moisture content in agrophytocenosis, serving as a crucial component of precision farming systems and agroecology. The integration of this technology promotes sustainable agricultural practices by minimizing water consumption while maximizing crop productivity. This aligns with broader environmental goals of conserving natural resources and reducing agricultural runoff. On a larger scale, data derived from such studies can inform policy decisions related to water resource management, guiding regulations that promote efficient water use in agriculture. Full article

One of the fundamental challenges in geophysics is the calculation of distribution models for physical properties in the subsurface that accurately reproduce the measurements obtained in the survey and are geologically plausible in the context of the study area. This is known as inverse modeling. Performing a 3D joint inversion of multimodal geophysical data is a computationally intensive task. Additionally, since it involves a modeling process, finding a solution that matches the desired characteristics requires iterative calculations, which can take days or even weeks to obtain final results. In this paper, we propose a robust numerical solution for 3D joint inversion of gravimetric and magnetic data with Gramian-based structural similarity and structural direction constraints using parallelization as a high-performance computing technique, which allows us to significantly reduce the total processing time based on the available Random-Access Memory (RAM) and Video Random-Access Memory (VRAM)and improve the efficiency of interpretation. The solution is implemented in the high-level programming languages Fortran and Compute Unified Device Architecture (CUDA) Fortran, capable of optimal resource management while being straightforward to implement. Through the analysis of performance and computational costs of serial, parallel, and hybrid implementations, we conclude that as the inversion domain expands, the processing speed could increase from 4× up to 100× times faster, rendering it particularly advantageous for applications in larger domains. We tested our algorithm with two synthetic data sets and field data, showing better results than standard separate inversion. The proposed method will be useful for joint geological and geophysical interpretation of gravimetric and magnetic data used in exploration geophysics for example minerals, ore, and petroleum search and prospecting. Its application will significantly increase the reliability of physical-geological models and accelerate the process of data processing. Full article

The Vale do Curaçá and Riacho do Pontal copper districts are located within the northern part of the Archaean São Francisco Craton and represent two pulses of mineralization. The copper districts have been identified as Iron-Oxide-Copper-Gold (IOCG) classes of deposits. An older metallogenic event associated with the Caraíba copper deposit, which is located in the Vale do Curaçá district, is related to Palaeoproterozoic (ca. 2 to 2.2 Ga) hydrothermal processes. A younger Neoproterozoic (ca. 750 to 570 Ma) episode of volcanism and associated plutonism is represented by the Riacho do Pontal mineral district. Seismic tomography data from across east-central Brazil show that the multiage Carajás province and Vale do Curaçá and Riacho do Pontal copper districts sit along either side of a prominent NW-trending upper lithospheric high-velocity zone. The edges of the high-velocity zone point to long-lived subparallel transcrustal structures that have been the focus of multiple reactivations and copper mineralization events. Regional gravity and magnetic maps show that the Vale do Curaçá copper district extends over an area greater than 110 km by 22 km. The magnetic and gravity values show significant variations correlated with this area. The district includes high gravity values associated with the Caraíba copper mine (>−35 mGal), which has a greater density (3.13 g/cm³) than the nonmineralized host rock density (2.98 g/cm³). The gravity anomaly signature over the Riacho do Pontal copper district is characterized by a 40-km long NW–SE trending Bouguer gravity low. The Ria4 occurrences of the Riacho do Pontal copper district are situated in these regional low-gravity domains. Data from regional airborne magnetic and ground gravity surveys were inverted to obtain a 3D magnetic susceptibility and density model, respectively, for the known districts. The results show that the Caraíba deposit is characterized by a both dense and magnetic source showing structural control by thrust shear zones. The 2D and 3D geological models show two main NNW prospective trends. Trends I and II have a sigmoidal shear shape and are positioned in the contact zone between domains with high magnetic susceptibility (SI > 0.005) and density > 0 g/cm³). Trend I is 40 km × 10 km in size and hosts the Caraíba, Surubim, and Vermelho copper mines and other minor deposits. The results obtained from the 3D magnetic inversion model for the region of the Riacho do Pontal district show weak magnetic anomaly highs extending along a NW–SE magnetic gradient trend. The gradient is related to mapped shear zones that overprint older and deeper NE–SW features of the São Francisco cratonic root. The area includes high gravity values associated with the Caraíba copper deposit, which has a greater density (3.13 g/cm³) than the nonmineralized host rock density (2.4 g/cm³). Full article