A contribution to aeromagnetic deculturing in populated areas

Modern regional airborne magnetic data sets when acquired in populated areas are inevitably degraded by cultural interference. In the UK 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 a manual assessment and refinement of the acquired database. Here we present an improved component of that procedure that guides the detection of localised 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 UK 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 data set. 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 UK aeromagnetic data

Advanced Geoscience Remote Sensing

Nowadays, advanced remote sensing technology plays tremendous roles to build a quantitative and comprehensive understanding of how the Earth system operates. The advanced remote sensing technology is also used widely to monitor and survey the natural disasters and man-made pollution. Besides, telecommunication is considered as precise advanced remote sensing technology tool. Indeed precise usages of remote sensing and telecommunication without a comprehensive understanding of mathematics and physics. This book has three parts (i) microwave remote sensing applications, (ii) nuclear, geophysics and telecommunication; and (iii) environment remote sensing investigations

Shear-wave and spatial attributes in time-lapse 3-D/3-C seismic and potential-field datasets

In this study, I utilize multicomponent time-lapse seismic datasets for investigating subtle seismic properties of Weyburn reservoir undergoing enhanced oil recovery and geologic sequestration of CO2. The primary focus is on extracting shear-wave information from surface three-dimensional and three-component (3-D/3-C) reflection datasets. Four groups of interrelated objectives are addressed: 1) calibrated and true-amplitude processing of multicomponent time-lapse seismic data, 2) extraction of amplitude variations with angle (AVA) and offset (AVO) attributes for separating pressure and fluid-saturation effects within the reservoir, 3) development of receiver-function methods for investigating the shallow subsurface, and 4) 2-D spatial pattern analysis of attribute maps, intended for automated interpretation of the results and a new type of AVO analysis. To achieve the first of these objectives, I reprocess the field surface 3-C/3-D reflection datasets by using pre-stack waveform calibration followed by complete reflection processing using commercial ProMAX software. For the second, principal objective of this study, several AVA attributes of the reservoir are examined, including those related to P- and P/S- converted waves and P- and S-wave impedances. The amplitudes and AVA attributes derived from seismic data indicate temporal variations potentially caused by pore-pressure and CO2-saturation variations within the reservoir. By comparing with AVA forward models, the seismic data suggest correlations between the increasing pore pressure and decreasing AVA intercepts and increasing AVA gradients. Increasing CO2 saturations appear to correlate with simultaneously decreasing AVA intercepts and gradients. CO2-saturated zones are thus interpreted as Class III AVA anomalies. In order to take further advantage from 3-C recordings and investigate advanced methods for S-wave seismic data analysis, receiver functions are used to study the shallow near-surface structure. This is apparently the first application of this method to reflection seismic datasets on land and in a time-lapse 3-D dataset. I show that it is feasible and useful to measure the near-surface S-wave velocity structure by using multi-component seismic data. From Weyburn reflection data, the average mapped receiver-function time lags are about 35 ms, which corresponds to near-surface S-wave velocities of about 550 m/s. Time-lapse variations of the near-surface structure are measured, and S-wave statics models are derived. Such models can be useful for converted-wave seismic imaging. The last objective of this Dissertation is to develop tools for interpretation of gridded 2-D spatial images, such as mapping AVO attribute quantitatively and automatically. For this purpose, a new pattern-recognition approach called skeletonization is developed and applied to several regional aeromagnetic and gravity images from southern Saskatchewan and Manitoba. The approach is combined with 2-D empirical mode decomposition allowing pattern analysis at variable spatial scales. The results show that skeletonization helps identifying complex geologic structures and measuring their quantitative attributes that are not available from conventional interpretation. Applications of this approach to interpretation of AVO attributes are discussed

Potential anomaly separation and archeological site localization using genetically trained multi-level cellular neural networks

In this paper, a supervised algorithm for the evaluation of geophysical sites using a multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. ML-CNN is a stochastic image processing technique based on template optimization using neighborhood relationships of the pixels. The separation/enhancement and border detection performance of the proposed method is evaluated by various interesting real applications. A genetic algorithm is used in the optimization of CNN templates. The first application is concerned with the separation of potential field data of the Dumluca chromite region, which is one of the rich reserves of Turkey; in this context, the classical approach to the gravity anomaly separation method is one of the main problems in geophysics. The other application is the border detection of archeological ruins of the Hittite Empire in Turkey. The Hittite civilization sites located at the Sivas-Altinyayla region of Turkey are among the most important archeological sites in history, one reason among others being that written documentation was first produced by this civilization

Improved techniques in data analysis and interpretation of potential fields: examples of application in volcanic and seismically active areas

Geopotential data may be interpreted by many different techniques, depending on the nature of the mathematical equations correlating specific unknown ground parameters to the measured data set. The investigation based on the study of the gravity and magnetic anomaly fields represents one of the most important geophysical approaches in the earth sciences. It has now evolved aimed both at improving of known methods and testing other new and reliable techniques. This paper outlines a general framework for several applications of recent techniques in the study of the potential methods for the earth sciences. Most of them are here described and significant case histories are shown to illustrate their reliability on active seismic and volcanic areas

2D Continuous Wavelet Transform of potential fields due to extended source distributions

AbstractWe analyse the real Continuous Wavelet Transform 2D (CWT2D) of potential fields for the investigation of potential field singularities. We focus our attention to extended geological sources, in order to verify the reliability of this method with realistic fields. 3D space-scale representation (3D Scalogram) related to synthetic models were generated, showing the Wavelet Transform Modulus Maxima (WTMM) at each scale. The WTMM are related to the shape of the source, so defining some sort of source boundary analysis through the CWT. Wavelets of different order may help to gain resolution and define source features. Selecting a range of scales where the sources behave as if they are approximately isolated, the depth to the source may be estimated basing on the property that the lines joining the modulus maxima of the wavelet coefficients at different scales (WTMML) intersect each other at the edges of the causative body. Therefore, it is possible to manage the information contained in the wavelet transform of fields related to extended sources. In the real case of the anomaly gravity map of the Vesuvius area (Italy), we estimated the depth of the Mesozoic carbonate basement in the Pompei Basin. We showed also how the WTMML information can be integrated to that of another multiscale method, the Depth from Extreme Points (DEXP) transformation, which is also related to the source density distribution of a given region

Advanced Sensing, Fault Diagnostics, and Structural Health Management

Advanced sensing, fault diagnosis, and structural health management are important parts of the maintenance strategy of modern industries. With the advancement of science and technology, modern structural and mechanical systems are becoming more and more complex. Due to the continuous nature of operation and utilization, modern systems are heavily susceptible to faults. Hence, the operational reliability and safety of the systems can be greatly enhanced by using the multifaced strategy of designing novel sensing technologies and advanced intelligent algorithms and constructing modern data acquisition systems and structural health monitoring techniques. As a result, this research domain has been receiving a significant amount of attention from researchers in recent years. Furthermore, the research findings have been successfully applied in a wide range of fields such as aerospace, manufacturing, transportation and processes