AIRRLS: An Augmented Iteratively Re-weighted and Refined Least Squares Algorithm for Inverse Modeling of Magnetometry Data

This work aims to examine the functionality of a new Augmented Iteratively Re-weighted and Refined Least Squares algorithm (AIRRLS) togenerate a 3D model of magnetic susceptibility property from a potentialfield magnetometry survey. Whereby this algorithm ameliorates an lpnorm Tikhonov regularization cost function through replacing a set ofweighted linear system of equations. It leads to constructing a magneticsusceptibility model that iteratively converges to an optimum solution,meanwhile the regularization parameter performs as a stopping criterionto finalize the iterations. To tackle and suppress the intrinsic tendency ofa sought target responsible for generating a magnetic anomaly and to notbe imaged at shallow depth in inverse modeling, a prior depth weightingfunction is imposed in the principle system of equations. The significanceof this research lies in improvement of the performance of the inversion,where the running time of an lp norm problem after incorporating apre-conditioner conjugate gradient solver (PCCG) in cases of large scalegeophysical dataset. Forasmuch as this study attempts to image a geological target with low magnetic susceptibility property, it is assumed thatthere is no remanent magnetization. The applicability of the algorithm istested for a synthetic multi-source data to demonstrate its performancein 3D modeling . Subsequently, a real case study in Semnan provinceof Iran, is investigated to image an embedded porphyry copper layerin a sequence of sediments. The sought target consists of a concealedarc-shaped porphyry andesite unit that may have potential of Cuoccurrences. Results prove that it extends down at depth, so exploratorydrilling is highly recommended to get insights about its potential forCu-bearing mineralization

HEBF strategy: A hybrid evidential belief function in geospatial data analysis for mineral potential mapping

In integrating geospatial datasets for mineral potential mapping (MPM), the uncertainty model of MPM can be inferred from the Dempster – Shafer rules of combination. In addition to generating the uncertainty model, evidential belief functions (EBFs) present the belief, plausibility, and disbelief of MPM, whereby four models can be simultaneously utilized to facilitate the interpretation of mineral favourability output. To investigate the functionality and applicability of the EBFs, we selected the Naysian porphyry copper district located on the Urmia – Dokhtar magmatic belt in the northeast of Isfahan city, central Iran. Multidisciplinary datasets- that are geochemical and geophysical data, ASTER satellite images, Quickbird, and ground survey- were designed in a geospatial database to run MPM. Implementing the Dempster law through the intersection (And) and union (OR) operators led to different MPM performances. To amplify the accuracy of the generated favourability maps, a combinatory EBFs technique was applied in three ways: (1) just OR operator, (2) just And operator, and (3) combination of And and OR operators. The plausibility map (as mineral favourability map) was compared to Cu productivity values derived from drilled boreholes, where the MPM accuracy of the hybrid method was higher than each operator. Of note, the success rate of the hybrid method validated by 21 boreholes was about 84%, and it demarcates high favourability zones occupying 0.67 km2 of the studied area

Geoelectrical characterization of a landslide surface for investigating hazard potency, a case study in the Tehran- North freeway, Iran

Landslide, as a geohazard issue, causes enormous threats to human lives and properties. In order to characterize the subsurface prone to the landslide which is occurred in the Tehran-North freeway, Iran, a comprehensive study focused on geological field observations, and a geoelectrical survey as a cost-effective and fast, non-invasive geophysical measurement was conducted in the area. As a result of road construction, problems in this region have increased. The Vertical Electrical Sounding (VES) investigation in the landslide area has been carried out by the Schlumberger array for data acquisition, implementing eight survey profiles varying in length between 60 and 130 m. Based on the electrical resistivity models through a smoothness-constrained least-square inversion methodology, the landslide structure (i.e., depth of the mobilized material and potential sliding surface) is better defined. The inferred lithological units, accompanied by stratigraphical data from a borehole and geological investigations for the prone landslide region, consisted of a discontinuous slip surface, having a wide range of resistivity, observed to be characterized by tuff with silt. Electrical resistivity values above 150 Ωm indicate a basement of weathered marlstone and sand. Values between 15 and 150 Ωm illustrate a shale-content layer with outcrops in the area that is the reason for movement. The sliding surface is at a depth of about 12 m. The method used in this study is a good candidate to investigate the risk of landslides in this region and can be applied to other landslide areas where borehole exploration is inefficient and expensive due to local complications

3D inversion of magnetic data using Lanczos bidiagonalization and unstructured element

This work presents an algorithm to construct a 3D magnetic susceptibility property from magnetic geophysical data. Physical model discretization has substantial impact on accurate inverse modeling of the sought sources in potential field geophysics, where structural meshing suffers from edge preserving of complex-shaped geological sources. In potential field geophysics, a finite-element (FE) methodology is usually employed to discretize the desired physical model domain through an unstructured mesh. The forward operator is calculated through a Gauss-Legendre quadrature technique rather than an analytic equation. To stabilize mathematical procedure of inverse modeling and cope with the intrinsic non-uniqueness arising from magnetometry data modeling, regularization is often implemented by utilizing a norm-based Tikhonov cost function. A so-called fast technique, “Lanczos Bidiagonalization (LB) algorithm”, can be utilized to solve the central system of equations derived from optimizing the function, where it decreases the execution time of the inverse problem by replacing the forward matrix with a lower dimension one. In addition, to obtain best regularization parameter, a weighted generalized cross-validation (WGCV) curve is plotted, that makes a balance between misfit norm and model norm introduced in the cost function. In order to tackle the normal propensity of physical structures to focus at the shallow depth, an expression of depth weighting is used. This procedure is applied to a synthetic scenario presenting a complex-shaped geometry along with a real set of magnetic data in central part of Iran. So the capability of the proposed algorithm for inversion indicates the accuracy of the inversion algorithm. Additionally, the modeling results pertaining to a field case study are in good agreement with the drilling data

Implications on oil trapping in the Kifl field of Iraq through geophysical investigations

Potential field geophysical measurements were conducted in the west of Kifl region in central Iraq to image a plausible oil-trapping reservoir. Ground-based magnetometry and gravimetry surveys were conducted to investigate this region by covering an area of 16  24 km by designing a regular grid spacing of 250 m. After preprocessing potential field data, different filters were utilized to separate the residuals from the regional anomalies. The complicated tectonic setting of the studied area was imaged by recognition of the fault system through simulation of the magnetic and gravity anomalies, which facilitates the configuration display of the oil-trapping mechanism. The geometry of a fault system was derived from parametric inversion of gravity data. The magnetic anomalies were extended with the trends of NS, NW, and NE and reached a maximum value of 55 nT. However, the gravity anomalies appeared with the same extensions and values ranging from -3.3 to 1.5 mGal. The intense magnetic susceptibility amount of the reservoir rocks is arising from chemical processes and iron-oxide ion replacements, accompanied by the migration and accumulation of hydrocarbon. Incorporating the results from the Euler’s depth estimation, parametric data modeling along with logging data assisted simultaneous modeling of the magnetic and gravity data. The 2D geological model of the subsurface layers at the Kifl area presents a graben-horst fault system within a thick sequence of sediment. Geological characteristics extracted from geophysical data modeling provided insightful information on the nature and essence of the hydrocarbon reservoirs in the Kifl area. It has formed through tectonic deformation and tension over the Arabian plate during the Permian – Paleocene cycle. Hence, it can be concluded that the aforementioned fault system has divided the hydrocarbon reservoirs

Prospective Acid Reflux Study of Iran (PARSI): Methodology and study design

<p>Abstract</p> <p>Background</p> <p>Gastroesophageal reflux disease is a common and chronic disorder but long term, prospective studies of the fate of patients seeking medical advice are scarce. This is especially prominent when looking at non-erosive reflux disease (NERD) patients.</p> <p>Methods</p> <p>We designed a prospective cohort to assess the long term outcome of GERD patients referring to gastroenterologists. Consecutive consenting patients, 15 years of age and older, presenting with symptoms suggestive of GERD referring to our outpatient clinics undergo a 30 minute interview. Upper gastrointestinal endoscopy is performed for them with protocol biopsies and blood samples are drawn. Patients are then treated according to a set protocol and followed regularly either in person or by telephone for at least 10 years.</p> <p>Discussion</p> <p>Our data show that such a study is feasible and follow-ups, which are the main concern, can be done in a fairly reliable way to collect data. The results of this study will help to clarify the course of various subgroups of GERD patients after coming to medical attention and their response to treatment considering different variables. In addition, the basic symptoms and biological database will fuel further molecular epidemiologic studies.</p

A comparative analysis of multi-index overlay and fuzzy ordered weighted averaging methods for porphyry Cu prospectivity mapping using remote sensing data: the case study of Chahargonbad area, SE of Iran

One of the specific features of porphyry copper (Cu) mineralization is the distinct occurrence of hydrothermal alteration zones, which can be mapped by processing various satellite images. Among free multispectral images, Landsat 8 OLI and ASTER data are known to be efficient in mapping different geological features, such as alteration zones and tectonic lineaments. This study aims to show the potential of these data types in mapping porphyry Cu mineralization by proposing a framework for employing and integrating different image processing methods. These methods include principal component analysis (PCA), spectral angle mapper (SAM), and matched filtering (MF) employed on these satellite images to map target al.teration zones. Moreover, PCA and directional filtering are applied to the ASTER dataset to enhance and map structural features. The results are evaluated and then combined to provide a potential map of Cu mineralization in the Chahargonbad area, located within the Urumieh-Dokhtar magmatic belt (UDMB) in Kerman province, Iran. The prediction-area plot and normalized density, which are data-driven methods, are used to assign the relative weight of each layer and evaluate them. Finally, using the calculated weights, data-driven multi-index overlay (DMIO) and fuzzy ordered weighted averaging (FOWA) methods are applied to combine the evidential layers. The potential mineralization maps created by the DMIO and FOWA provide a prediction rate of 80% and 82%, respectively. Furthermore, the accuracy of the integrated maps is investigated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curves. The AUC scores obtained from the ROC curves of DMIO and FOWA methods are 0.85 and 0.88, respectively, representing powerful positive spatial relationships with mineralization areas. Based on the results, the proposed framework can be applied to provide a potential map of porphyry Cu mineralization, particularly in arid regions, with reasonable accuracy

3D Inversion of Magnetic Data through Wavelet based Regularization Method

This study deals with the 3D recovering of magnetic susceptibility model by incorporating the sparsity-based constraints in the inversion algorithm. For this purpose, the area under prospect was divided into a large number of rectangular prisms in a mesh with unknown susceptibilities. Tikhonov cost functions with two sparsity functions were used to recover the smooth parts as well as the sharp boundaries of model parameters. A pre-selected basis namely wavelet can recover the region of smooth behaviour of susceptibility distribution while Haar or finite-difference (FD) domains yield a solution with rough boundaries. Therefore, a regularizer function which can benefit from the advantages of both wavelets and Haar/FD operators in representation of the 3D magnetic susceptibility distributionwas chosen as a candidate for modeling magnetic anomalies. The optimum wavelet and parameter β which controls the weight of the two sparsifying operators were also considered. The algorithm assumed that there was no remanent magnetization and observed that magnetometry data represent only induced magnetization effect. The proposed approach is applied to a noise-corrupted synthetic data in order to demonstrate its suitability for 3D inversion of magnetic data. On obtaining satisfactory results, a case study pertaining to the ground based measurement of magnetic anomaly over a porphyry-Cu deposit located in Kerman providence of Iran. Now Chun deposit was presented to be 3D inverted. The low susceptibility in the constructed model coincides with the known location of copper ore mineralization