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The method of layer matrices is applied to solve the problem of the static deformation of a multilayered elastic half‐space by buried sources. Each layer of the multilayered medium is assumed to be homogeneous and isotropic, and the interfaces are assumed to be in welded contact. The point source ia represented as a discontinuity in the z‐dependent coefficients of the displacement and stress integrands at the source level. Source functions are obtained for the six elementary displacement dislocations. Explicit expressions for the surface displacements are calculated for a vertical strike‐slip and a vertical dip‐slip fault.

The propagation of plane waves in fibre-reinforced, anisotropic, elastic media is discussed. The expressions for the phase velocity of quasi-P (qP ) and quasi-SV (qSV ) waves propagating in a plane containing the reinforcement direction are obtained as functions of the angle between the propagation and reinforcement directions. Closed form expressions for the amplitude ratios for qP and qSV waves reflected at the free surface of a fibre-reinforced, anisotropic, homogeneous, elastic half-space are obtained. These expressions are used to study the variation of amplitude ratios with angle of incidence. It is found that reinforcement has a significant effect on the amplitude ratios and critical angle.

SUMMARY Closed‐form expressions for the displacements and stresses at an arbitrary point of a homogeneous, isotropic, perfectly elastic half‐space caused by a dip‐slip line source obtained earlier are integrated analytically to derive the elastic residual field due to a long dip‐slip fault of finite width. The results are valid for an arbitrary dip of the fault and for arbitrary receiver locations inside the medium. The variation of the displacement and stress field with the distance from the fault is studied numerically. Contour maps showing the stress field around a long dip‐slip fault are obtained. Permanent surface deformations which occur as a result of faulting can be measured from geodetic surveys carried out before and after an earthquake. These observations can be used to obtain the fault parameters (dip, slip, width, depth) by inversion, using the theoretical expressions given in the paper. The features of the observational data which are diagnostic of the source properties are: the asymmetry of the data; the magnitude of various components of deformation; and the rate of fall of these components with distance. The asymmetry depends mainly on the dip, the magnitude on the slip and the rate of fall on the depth of the fault.

By using Volterra's relation, it is shown that a tangential dislocation in a gravitating radially inhomogeneous sphere can be characterized by discontinuities in the stress and displacement fields across the source surface r = r,,. This representation of the source facilitates the numerical evaluation of the displacement field.It is found that at the free surface of the Earth the six simultaneous linear differential equations governing the spheroidal field associated with the Legendre polynomial of the first degree (I = 1) degenerate into five.The two equations corresponding to the toroidal field for 1 = 1 degenerate into one. Therefore, when dealing with the case 1 = 1, one must incorporate additional conditions, namely, that the angular momentum of the sphere about its centre is zero and that the centre of mass of the sphere is not displaced.The changes in the inertia tensor due to an earthquake of arbitrary depth and orientation are calculated with the assumption that the Adams-Williamson condition holds at the core. No difference in the numerical results are obtained if the Adams-Williamson conditions does not hold. Comparison with homogeneous, non-gravitating Earth model shows that, in general, real Earth models render a smaller value for the changes in the inertia tensor. It appears from our results that earthquakes are insufficient to maintain the Chandler wobble.

The treatment of boundary value problems in various vector-separable regimes is unified and facilitated with the use of the eigenvector expansion of their corresponding Green's tensors. In particular, the method is useful for the vector Laplace, Poisson, Helmholtz and NaviCr equations in spherical and cylindrical polars.Several examples are given; among them, an evaluation of the dynamic and static response of an elastic sphere to shear dislocations requires particular mention.It is found that the static displacement field in a sphere which is associated with the Legendre polynomial of the first degree (Z = 1) poses some problems. In such a case, one must incorporate additional conditions, namely, that the angular momentum of the sphere about its centre is zero and that the centre of mass of the sphere is not displaced. It is recommended that eigenvector expansions be adopted in geophysical theory. Its inherent elegance and compactness make it an excellent tool for the construction of theoretical Earth-models.

The Raageshwari Deep Gas Field is located in the Central Basin High, in the southern part of the Barmer Basin, Rajasthan, India. The major reservoirs are eruptive volcanics and subsequently deposited clastics of Cretaceous - Early Tertiary age. The reservoirs are micro porosity-low permeability gas condensate systems. Exploration wells were conventionally tested with gas production rates of 2–4 MMScf/day at high drawdowns. In the development phase, deviated wells with multi-stage hydraulic fracturing have shown multi-fold improvement in production performance. Volcanic reservoirs are characterized by quick changes of lithofacies both laterally and vertically resulting in strong vertical and horizontal heterogeneity. Unpredictable distributions of pore and fracture networks resulted in variable well performance and productivities. Difficulties in reservoir characterization pose an immense challenge to effective well and reservoir management. Comprehensive reservoir characterization studies were undertaken to unravel the complexity of the volcanic reservoirs and to capture the uncertainties. The workflow integrates data from volcanic outcrop analogues, conventional core (visual description, thin section petrography, geochemistry, RCA, Dean Stark and SCAL), mudlogs (gas shows and chromatography), and wireline logs including dipole sonic, image and NMR logs. Productive reservoir units deliverability was validated with production logs, whereas the effectiveness of hydraulic fracturing was matched with micro-seismic data coupled with seismic attributes (AntTrack volume). Matrix permeability coupled with fracture characterization was used to match well performance. Spatial distributions of reservoir properties were populated by geostatistical techniques incorporating available geometries and flow unit dimensions from analogues and well information. The validity of this approach has been confirmed with most recent wells as blind tests and a successful production test from a deeper unit. The approach also emphasises the importance of integrating different datasets for detailed reservoir characterization leading to increased confidence in effective reservoir management of this complex reservoir.

Soil is an important parameter affecting crop yield prediction. Analysis of soil nutrients can aid farmers and soil analysts to get higher yield of the crops by making prior arrangements. In this paper, various machine learning techniques have been implemented in order to predict Mustard Crop yield in advance from soil analysis. Data for the experimental setup has been collected from Department of Agriculture Department, Talab Tillo, Jammu; comprising soil samples of different districts of Jammu region for Mustard crop. For the current study, five supervised machine learning techniques namely K-Nearest Neighbor (KNN), Naïve Bayes, Multinomial Logistic Regression, Artificial Neural Network (ANN) and Random Forest have been applied on the collected data. To assess the performance of each technique under study; five parameters namely accuracy, recall, precision, specificity and f-score have been evaluated. Experimentation has been carried out to make known the most accurate technique for mustard crop yield prediction. From experimental results, it has been predicted that KNN and ANN (among the undertaken ML techniques for the study) found to be most accurate techniques for mustard crop yield prediction.