In deep mineral exploration, the acquisition of audio magnetotelluric (AMT) data is severely affected by ambient noise near the observation sites; This near-field noise restricts investigation depths. Mathematical morphological filtering (MMF) proved effective in suppressing large-scale strong and variably shaped noise, typically low-frequency noise, but can not deal with pulse noise of AMT data. We combine compressive sensing and MMF. First, we use MMF to suppress the large-scale strong ambient noise; second, we use the improved orthogonal match pursuit (IOMP) algorithm to remove the residual pulse noise. To remove the noise and protect the useful AMT signal, a redundant dictionary that matches with spikes and is insensitive to the useful signal is designed. Synthetic and field data from the Luzong field suggest that the proposed method suppresses the near-source noise and preserves the signal well; thus, better results are obtained that improve the output of either MMF or IOMP.
Conventional f-x empirical mode decomposition (EMD) is an effective random noise attenuation method for use with seismic profiles mainly containing horizontal events. However, when a seismic event is not horizontal, the use of f-x EMD is harmful to most useful signals. Based on the framework of f-x EMD, this study proposes an improved denoising approach that retrieves lost useful signals by detecting effective signal points in a noise section using local similarity and then designing a weighting operator for retrieving signals. Compared with conventional f-x EMD, f-x predictive filtering, and f-x empirical mode decomposition predictive filtering, the new approach can preserve more useful signals and obtain a relatively cleaner denoised image. Synthetic and field data examples are shown as test performances of the proposed approach, thereby verifying the effectiveness of this method.
In this paper, magnesium–lanthanum powders were synthesized by an electrodeposition technique using an aqueous solution, based on magnesium chloride hexahydrate and lanthanum nitrate for different values of voltage and La weight percentage. A copper cathode plate and a tungsten thread anode were used for the preparation of the Mg–La layers. The as-deposited powders were characterized by energy dispersive spectroscopy (EDS) to determine the chemical composition, scanning electron microscope to describe the morphology, X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectra in order to define the chemical structure. EDS analyses indicate the presence of three elements (Mg, La and O) in the different deposited layers, and the major one is O (51–74.2 at.%). The two other elements, Mg and La, are, respectively, ranked 2 and 3 in the different powders. Morphological description reveals the formation of heterogeneous chemical structures on the surfaces of specimens. They are characterized by aggregates with different sizes. The dark aggregates are associated with magnesium, and the bright ones are attributed to lanthanum. X-ray results showed the existence of two distinct phases in the obtained deposits which are magnesium hydroxide (Mg(OH)2) and lanthanum hydroxide (La(OH)3). FTIR analyses confirm the presence of the two phases identified in XRD diffractograms, and they can be exhibited by clear peaks. In the studied ranges of voltage and La weight percentage, their peak transmittances have non-monotonic behaviors. A design of experiments was used to determine the influence of these two processing parameters and their interaction on the products formation. The parameter effects were ranked as follow: The first was the voltage then the interaction between the two parameters and finally the La content.
Pore structure characteristics are important to oil and gas exploration in complex low-permeability reservoirs. Using multifractal theory and nuclear magnetic resonance (NMR), we studied the pore structure of low-permeability sandstone rocks from the 4th Member (E-S4) of the Shahejie Formation in the south slope of the Dongying Sag. We used the existing pore structure data from petrophysics, core slices, and mercury injection tests to classify the pore structure into three categories and five subcategories. Then, the T (2) spectra of samples with different pore structures were interpolated, and the one- and three-dimensional fractal dimensions and the multifractal spectrum were obtained. Parameters alpha (intensity of singularity) and f (alpha) (density of distribution) were extracted from the multifractal spectra. The differences in the three fractal dimensions suggest that the pore structure types correlate with alpha and f (alpha). The results calculated based on the multifractal spectrum is consistent with that of the core slices and mercury injection. Finally, the proposed method was applied to an actual logging profile to evaluate the pore structure of low-permeability sandstone reservoirs.
Accurate salt dome detection from 3D seismic data is crucial to different seismic data analysis applications. We present a new edge based approach for salt dome detection in migrated 3D seismic data. The proposed algorithm overcomes the drawbacks of existing edge-based techniques which only consider edges in the x (crossline) and y (inline) directions in 2D data and the x (crossline), y (inline), and z (time) directions in 3D data. The algorithm works by combining 3D gradient maps computed along diagonal directions and those computed in x, y, and z directions to accurately detect the boundaries of salt regions. The combination of x, y, and z directions and diagonal edges ensures that the proposed algorithm works well even if the dips along the salt boundary are represented only by weak reflectors. Contrary to other edge and texture based salt dome detection techniques, the proposed algorithm is independent of the amplitude variations in seismic data. We tested the proposed algorithm on the publicly available Netherlands offshore F3 block. The results suggest that the proposed algorithm can detect salt bodies with high accuracy than existing gradient based and texture-based techniques when used separately. More importantly, the proposed approach is shown to be computationally efficient allowing for real time implementation and deployment.