Separation of magnetic anomalies into induced and remanent magnetization contributions

Inversion of magnetic data is complicated by the presence of remanent magnetization, and it provides limited information about the magnetic source because of the insufficiency of data and constraint information. We propose a Fourier domain transformation allowing the separation of magnetic anomalies into the components caused by induced and remanent magnetizations. The approach is based on the hypothesis that each isolated source is homogeneous with a uniform and specific Koenigsberger ratio. The distributions of susceptibility and remanent magnetization are subsequently recovered from the separated anomalies. Anomaly components, susceptibility distribution and distribution of the remanent and total magnetization vectors (direction and intensity) can be achieved through the processing of the anomaly components. The proposed method therefore provides a procedure to test the hypotheses about target source and magnetic field, by verifying these models based on available information or a priori information from geology. We test our methods using synthetic and real data acquired over the Zhangfushan iron-ore deposit and the Yeshan polymetallic deposit in eastern China. All the tests yield favourable results and the obtained models are helpful for the geological interpretation.     

Application of Hilbert‐like transforms for enhanced processing of full tensor magnetic gradient data

Commonly, geomagnetic prospection is performed via scalar magnetometers that measure values of the total magnetic intensity. Recent developments of superconducting quantum interference devices have led to their integration in full tensor magnetic gradiometry systems consisting of planar‐type first‐order gradiometers and magnetometers fabricated in thin‐film technology. With these systems measuring directly the magnetic gradient tensor and field vector, a significantly higher magnetic and spatial resolution of the magnetic maps is yield than those produced via conventional magnetometers. In order to preserve the high data quality in this work, we develop a workflow containing all the necessary steps for generating the gradient tensor and field vector quantities from the raw measurement data up to their integration into high­resolution, low­noise, and artefactless two‐dimensional maps of the magnetic field vector. The gradient tensor components are processed by superposition of the balanced gradiometer signals and rotation into an Earth‐centred Earth‐fixed coordinate frame. As the magnetometers have sensitivity lower than that of gradiometers and the total magnetic intensity is not directly recorded, we employ Hilbert‐like transforms, e.g., integration of the gradient tensor components or the conversion of the total magnetic intensity derived by calibrated magnetometer readings to obtain these values. This can lead to a better interpretation of the measured magnetic anomalies of the Earth's magnetic field that is possible from scalar total magnetic intensity measurements. Our conclusions are drawn from the application of these algorithms on a survey acquired in South Africa containing full tensor magnetic gradiometry data.     

Reorientation of three‐component borehole magnetic data

Three‐component borehole magnetics provide important additional information compared to total field or horizontal and vertical measurements. These data can be used for several tasks such as the localization of ferromagnetic objects, the determination of apparent polar wander curves and the computation of the magnetization of rock units. However, the crucial point in three‐component borehole magnetics is the reorientation of the measured data from the tool's frame to the geographic reference frame North, East and Downwards. For this purpose, our tool, the Göttinger Borehole Magnetometer, comprises three orthogonally aligned fibre optic gyros along with three fluxgate sensors. With these sensors, the vector of the magnetic field along with the tool rotation can be recorded continuously during the measurement. Using the high–precision gyro data, we can compute the vector of the magnetic anomaly with respect to the Earth's reference frame. Based on the comparison of several logs measured in the Outokumpu Deep Drill Hole (OKU R2500, Finland), the repeatability of the magnetic field vector is 0.8° in azimuthal direction, 0.08° in inclination and 71 nT in magnitude.     

Levelling aeromagnetic survey data without the need for tie‐lines

A new methodology that levels airborne magnetic data without orthogonal tie‐lines is presented in this study. The technique utilizes the low‐wavenumber content of the flight‐line data to construct a smooth representation of the regional field at a scale appropriate to the line lengths of the survey. Levelling errors are then calculated between the raw flight‐line data and the derived regional field through a least squares approach. Minimizing the magnitude of the error, with a first‐degree error function, results in significant improvements to the unlevelled data. The technique is tested and demonstrated using three recent airborne surveys.     

A contribution to aeromagnetic deculturing in populated areas

Modern regional airborne magnetic datasets, when acquired in populated areas, are inevitably degraded by cultural interference. In the United Kingdom context, the spatial densities of interfering structures and their complex spatial form severely limit our ability to successfully process and interpret the data. Deculturing procedures previously adopted have used semi‐automatic methods that incorporate additional geographical databases that guide manual assessment and refinement of the acquired database. Here we present an improved component of that procedure that guides the detection of localized responses associated with non‐geological perturbations. The procedure derives from a well‐established technique for the detection of kimberlite pipes and is a form of moving‐window correlation using grid‐based data. The procedure lends itself to automatic removal of perturbed data, although manual intervention to accept/reject outputs of the procedure is wise. The technique is evaluated using recently acquired regional United Kingdom survey data, which benefits from having an offshore component and areas of largely non‐magnetic granitic response. The methodology is effective at identifying (and hence removing) the isolated perturbations that form a persistent spatial noise background to the entire dataset. Probably in common with all such methods, the technique fails to isolate and remove amalgamated responses due to complex superimposed effects. The procedure forms an improved component of partial automation in the context of a wider deculturing procedure applied to United Kingdom aeromagnetic data.     

Estimating external magnetic field differences at high geomagnetic latitudes from a single station

Providing an accurate estimate of the magnetic field on the Earth's surface at a location distant from an observatory has useful scientific and commercial applications, such as in repeat station data reduction, space weather nowcasting or aeromagnetic surveying. While the correlation of measurements between nearby magnetic observatories at low and mid‐latitudes is good, at high geomagnetic latitudes () the external field differences between observatories increase rapidly with distance, even during relatively low magnetic activity. Thus, it is of interest to describe how the differences (or errors) in external magnetic field extrapolation from a single observatory grow with distance from its location. These differences are modulated by local time, seasonal and solar cycle variations, as well as geomagnetic activity, giving a complex temporal and spatial relationship. A straightforward way to describe the differences are via confidence intervals for the extrapolated values with respect to distance. To compute the confidence intervals associated with extrapolation of the external field at varying distances from an observatory, we used 695 station‐years of overlapping minute‐mean data from 37 observatories and variometers at high latitudes from which we removed the main and crustal fields to isolate unmodelled signals. From this data set, the pairwise differences were analysed to quantify the variation during a range of time epochs and separation distances. We estimate the 68.3%, 95.4% and 99.7% confidence levels (equivalent to the 1σ, 2σ and 3σ Gaussian error bounds) from these differences for all components. We find that there is always a small non‐zero bias that we ascribe to instrumentation and local crustal field induction effects. The computed confidence intervals are typically twice as large in the north–south direction compared to the east‐west direction and smaller during the solstice months compared to the equinoxes.     

The application of spatial derivatives to non‐potential field data interpretation

Source/body edge detection is a common feature in the processing and interpretation of potential field data sets. A wide range of spatial derivatives is available to enhance the information contained in the basic data. Here the ability of these procedures to assist with the mapping interpretation of non‐potential field data is considered. The study uses airborne electromagnetic (conductivity) data but also provides a general context for other conductivity/resistivity data, provided the non‐potential field nature of active and thus spatially‐focused, measurements is acknowledged. The study discusses and demonstrates the application of a range of common spatial derivative procedures, including the analytic signal and upward continuation, to both magnetic and conductivity data. The ability of the tilt derivative to provide enhanced mapping of conductivity data is considered in detail. Tilt and its associated functions are formed by taking combinations of vertical and horizontal derivatives of the data set. Theoretical forward modelling studies are first carried out to assess the performance of the tilt derivative in relation to the detection and definition of concealed conductivity structure. The tilt derivative embodies automatic gain control that normalizes the detection and definition of both weak and strong conductivity gradients across an appropriate subsurface depth range. The use of high‐order spatial derivatives inevitably results in a degree of noise (cultural perturbation) amplification that is survey and technique specific. Both of these aspects are considered using practical case studies of jointly obtained magnetic and conductivity data at a variety of spatial scales.     

Three‐dimensional receiver deghosting of seismic streamer data using L1 inversion and redundant extended radon dictionary

In this paper, we propose a novel three‐dimensional receiver deghosting algorithm that is capable of deghosting both horizontal and slanted streamer data in a theoretically consistent manner. Our algorithm honours wave propagation phenomena in a true three‐dimensional sense and frames the three‐dimensional receiver deghosting problem as a Lasso problem. The ultimate goal is to minimise the mismatch between the actual measurements and the simulated wavefield with an L1 constraint applied in the extended Radon space to handle the underdetermined nature of this problem. We successfully demonstrate our algorithm on a modified three‐dimensional EAGE/SEG Overthrust model and a Red Sea marine dataset.     

Estimating magnetic dike parameters using a non‐linear constrained inversion technique: an example from the Särna area,west central Sweden

In this paper, we describe a non‐linear constrained inversion technique for 2D interpretation of high resolution magnetic field data along flight lines using a simple dike model. We first estimate the strike direction of a quasi 2D structure based on the eigenvector corresponding to the minimum eigenvalue of the pseudogravity gradient tensor derived from gridded, low‐pass filtered magnetic field anomalies, assuming that the magnetization direction is known. Then the measured magnetic field can be transformed into the strike coordinate system and all magnetic dike parameters – horizontal position, depth to the top, dip angle, width and susceptibility contrast – can be estimated by non‐linear least squares inversion of the high resolution magnetic field data along the flight lines. We use the Levenberg‐Marquardt algorithm together with the trust‐region‐reflective method enabling users to define inequality constraints on model parameters such that the estimated parameters are always in a trust region. Assuming that the maximum of the calculated g_zz (vertical gradient of the pseudogravity field) is approximately located above the causative body, data points enclosed by a window, along the profile, centred at the maximum of g_zz are used in the inversion scheme for estimating the dike parameters. The size of the window is increased until it exceeds a predefined limit. Then the solution corresponding to the minimum data fit error is chosen as the most reliable one. Using synthetic data we study the effect of random noise and interfering sources on the estimated models and we apply our method to a new aeromagnetic data set from the Särna area, west central Sweden including constraints from laboratory measurements on rock samples from the area.     

Consistency of stress state,locations and source mechanisms of events induced by hydraulic fracturing: downhole monitoring

We present results of processed microseismic events induced by hydraulic fracturing and detected using dual downhole monitoring arrays. The results provide valuable insight into hydraulic fracturing. For our study, we detected and located microseismic events and determined their magnitudes, source mechanisms and inverted stress field orientation. Event locations formed a distinct linear trend above the stimulated intervals. Source mechanisms were only computed for high‐quality events detected on a sufficient number of receivers. All the detected source mechanisms were dip‐slip mechanisms with steep and nearly horizontal nodal planes. The source mechanisms represented shear events and the non‐double‐couple components were very small. Such small, non‐double‐couple components are consistent with a noise level in the data and velocity model uncertainties. Strikes of inverted mechanisms corresponding to the nearly vertical fault plane are (within the error of measurements) identical with the strike of the location trend. Ambient principal stress directions were inverted from the source mechanisms. The least principal stress, σ₃, was determined perpendicular to the strike of the trend of the locations, indicating that the hydraulic fracture propagated in the direction of maximum horizontal stress. Our analysis indicated that the source mechanisms observed using downhole instruments are consistent with the source mechanisms observed in microseismic monitoring arrays in other locations. Furthermore, the orientation of the inverted principal components of the ambient stress field is in agreement with the orientation of the known regional stress, implying that microseismic events induced by hydraulic fracturing are controlled by the regional stress field.     

Research note: deblended-data reconstruction using generalized blending and deblending models

We introduce a concept of generalized blending and deblending, develop its models and accordingly establish a method of deblended-data reconstruction using these models. The generalized models can handle real situations by including random encoding into the generalized operators both in the space and time domain, and both at the source and receiver side. We consider an iterative optimization scheme using a closed-loop approach with the generalized blending and deblending models, in which the former works for the forward modelling and the latter for the inverse modelling in the closed loop. We applied our method to existing real data acquired in Abu Dhabi. The results show that our method succeeded to fully reconstruct deblended data even from the fully generalized, thus quite complicated blended data. We discuss the complexity of blending properties on the deblending performance. In addition, we discuss the applicability to time-lapse seismic monitoring as it ensures high repeatability of the surveys. Conclusively, we should acquire blended data and reconstruct deblended data without serious problems but with the benefit of blended acquisition.     

Non-linear inversion of controlled source multi-receiver electromagnetic induction data for unexploded ordnance using a continuation method

This work adopts a continuation approach, based on path tracking in model space, to solve the non-linear least-squares problem for discrimination of unexploded ordnance (UXO) using multi-receiver electromagnetic induction (EMI) data. The forward model corresponds to a stretched-exponential decay of eddy currents induced in a magnetic spheroid. We formulate an over-determined, or under-parameterized, inverse problem. An example using synthetic multi-receiver EMI responses illustrates the efficiency of the method. The fast inversion of actual field multi-receiver EMI responses of inert, buried ordnances is also shown. Software based on the continuation method could be installed within a multi-receiver EMI sensor and used for near-real-time UXO decision-making purposes without the need for a highly-trained operator.     

Artificial neural networks for removal of couplings in airborne transient electromagnetic data

Modern airborne transient electromagnetic surveys typically produce datasets of thousands of line kilometres, requiring careful data processing in order to extract as much and as reliable information as possible. When surveys are flown in populated areas, data processing becomes particularly time consuming since the acquired data are contaminated by couplings to man‐made conductors (power lines, fences, pipes, etc.). Coupled soundings must be removed from the dataset prior to inversion, and this is a process that is difficult to automate. The signature of couplings can be both subtle and difficult to describe in mathematical terms, rendering removal of couplings mostly an expensive manual task for an experienced geophysicist. Here, we try to automate the process of removing couplings by means of an artificial neural network. We train an artificial neural network to recognize coupled soundings in manually processed reference data, and we use this network to identify couplings in other data. The approach provides a significant reduction in the time required for data processing since one can directly apply the network to the raw data. We describe the neural network put to use and present the inputs and normalizations required for maximizing its effectiveness. We further demonstrate and assess the training state and performance of the network before finally comparing inversions based on unprocessed data, manually processed data, and artificial neural network automatically processed data. The results show that a well‐trained network can produce high‐quality processing of airborne transient electromagnetic data, which is either ready for inversion or in need of minimal manual processing. We conclude that the use of artificial neural network scan significantly reduce the processing time and its costs by as much as 50%.     

Basement geology beneath the northeast Thelon Basin,Nunavut: insights from integrating new gravity,magnetic and geological data

Current models for unconformity‐associated uranium deposits predict fluid flow and ore deposition along reactivated faults in >1.76 Ga basement beneath Mesoproterozoic siliciclastic basins. In frontier regions such as the Thelon Basin in the Kivalliq region of Nunavut, little is known about the sub‐basin distribution of units and structures, making exploration targeting very tenuous. We constructed a geological map of the basement beneath the unconformity by extrapolating exposed features into the subsurface. The new map is constrained by detailed geological, geophysical, and rock property observations of outcrops adjacent to the basin and by aeromagnetic and gravity data over the geophysically transparent sedimentary basin. From rock property measurements, it is clear that the diverse magnetic and density characteristics of major rock packages provide quantitative three‐dimensional constraints. Gravity profiles forward modelled in four cross sections define broad synforms of the Amer Belt and Archean volcanic rocks that are consistent with the structural style outside the basin. Major lithotectonic entities beneath the unconformity include: supracrustal rocks of the Archean Woodburn Lake group and Marjorie Hills meta sedimentary gneiss and associated mixed granitoid and amphibolitic gneiss; the Amer Mylonite Zone and inferred mafic intrusions oriented parallel and sub‐parallel; other igneous intrusions of 2.6 Ga, 1.83 Ga, and 1.75 Ga vintage; and the <2.3 Ga to >1.84 Ga Amer Group. Four main brittle regional fault arrays (040°–060°, 075°–90°, 120°, and 150°) controlled development and preservation of the basin. The reactivated intersections of such faults along fertile basement units such as the Rumble assemblage, Marjorie Hills assemblage, Nueltin igneous rocks, and Pitz formation are the best targets for uranium exploration.     

Analysis and interpretation of anomalous conductivity and magnetic permeability effects in time domain electromagnetic data: Part II: Sμ-inversion

In the paper by Pavlov and Zhdanov [J. Appl. Geophys. (2001)], we demonstrated that anomalous magnetic permeability of an ore body could result in measurable anomalous effects in TDEM data, which can be used in geophysical exploration. In the current paper, we develop a new method of TDEM data interpretation, which allows simultaneous reconstruction of both electrical and magnetic properties of the rocks. The method is based on a generalization of the S-inversion technique [66th Ann. Int. Mtg., Soc. Expl. Geophys., Expanded Abstr. (1996) 1306; 68th Ann. Int. Mtg., Soc. Expl. Geophys., Expanded Abstr. (1998) 473; J. Appl. Geophys. (1999)] for models containing thin sheets with anomalous conductivity and anomalous magnetic permeability. We call this method Sμ-inversion. Numerical 3-D modeling results demonstrate that Sμ-inversion provides useful information about both subsurface conductivity and magnetic permeability distributions. It can be used as a new tool for imaging TDEM data in mineral exploration.     

Research Note: Frequency domain orthogonal projection filtration of surface microseismic monitoring data

We address the problem of increasing the signal-to-noise ratio during surface microseismic monitoring data processing. Interference from different seismic waves causes misleading results of microseismic event locations. Ground-roll suppression is particularly necessary. The standard noise suppression techniques assume regular and dense acquisition geometries. Many pre-processing noise suppression algorithms are designed for special types of noise or interference. To overcome these problems, we propose a novel general-purpose filtration method. The goal of this method is to amplify only the seismic waves that are excited in the selected target area and suppress all other signals. We construct a linear projector onto a frequency domain data subspace, which corresponds to the seismic emission of the target area. The novel filtration method can be considered an extension of the standard frequency–wavenumber flat wave filtration method for non-flat waves and arbitrary irregular receiver-position geometries. To reduce the effect of the uncertainty of the velocity model, we suggest using additional active shot data (typically the perforation shots), which provide static travel time corrections for the target area. The promising prospects of the proposed method are confirmed by synthetic and semi-synthetic data processing.     

鄂尔多斯盆地北部低信噪比资料的高分辨率处理

鄂尔多斯盆地北部地区地震地质条件复杂,造成原始地震资料信噪比低,分辨率低,前期的地震资料储层与含气性预测的成果达不到目前勘探开发的要求.本文针对鄂尔多斯盆地北部低信噪比地震资料的特点,提出了一套适合本区的高分辨率处理方法,通过解决静校正和去噪问题,应用反褶积、精细速度分析以及高精度动校正和叠加等处理技术,在保证信噪比的前提下,提高了地震资料的分辨率.     

Petrophysics and mineral exploration: a workflow for data analysis and a new interpretation framework

As mineral exploration seeks deeper targets, there will be a greater reliance on geophysical data and a better understanding of the geological meaning of the responses will be required, and this must be achieved with less geological control from drilling. Also, exploring based on the mineral system concept requires particular understanding of geophysical responses associated with altered rocks. Where petrophysical datasets of adequate sample size and measurement quality are available, physical properties show complex variations, reflecting the combined effects of various geological processes. Large datasets, analysed as populations, are required to understand the variations. We recommend the display of petrophysical data as frequency histograms because the nature of the data distribution is easily seen with this form of display. A petrophysical dataset commonly contains a combination of overlapping sub-populations, influenced by different geological factors. To understand the geological controls on physical properties in hard rock environments, it is necessary to analyse the petrophysical data not only in terms of the properties of different rock types. It is also necessary to consider the effects of processes such as alteration, weathering, metamorphism and strain, and variables such as porosity and stratigraphy. To address this complexity requires that much more supporting geological information be acquired than in current practice. The widespread availability of field portable instruments means quantitative geochemical and mineralogical data can now be readily acquired, making it unnecessary to rely primarily on categorical rock classification schemes. The petrophysical data can be combined with geochemical, petrological and mineralogical data to derive explanations for observed physical property variations based not only on rigorous rock classification methods, but also in combination with quantitative estimates of alteration and weathering. To understand how geological processes will affect different physical properties, it is useful to define three end-member forms of behaviour. Bulk behaviour depends on the physical properties of the dominant mineral components. Density and, to a lesser extent, seismic velocity show such behaviour. Grain and texture behaviour occur when minor components of the rock are the dominate controls on its physical properties. Grain size and shape control grain properties, and for texture properties the relative positions of these grains are also important. Magnetic and electrical properties behave in this fashion. Thinking in terms of how geological processes change the key characteristics of the major and minor mineralogical components allows the resulting changes in physical properties to be understood and anticipated.     

多源布格重力异常数据贝叶斯融合算法及其在川滇地区的应用

布格重力异常数据是研究地壳结构和变形的重要依据,由于观测手段、处理方法等存在差异,不同手段获得的布格重力异常可能存在数据噪声水平及起算基准不一致,从而引起多源布格重力异常数据难以有效融合的难题.为此,本文在传统等效源重力数据融合方法的基础上,通过引入贝叶斯参数优化准则,提出了一种新的多源布格重力异常融合算法.随后对川滇...