The Fuyang oil-layer in North Songliao Basin is characterized by thin interbedded sands and shales, strong lateral variation, strong reservoir heterogeniety, and so on. The thickness of individual sand layers is generally 3–5 m. Identifying the channel sand-bodies of the Fuyang oil layer using seismic techniques is very difficult due to the low seismic resolution. Taking the GTZ area as an example, we discuss the genetic characteristics of the channel sand-bodies and point out the real difficulty in using seismic techniques to predict the channel sand-bodies. Two methods for the identification of channels are presented: frequency spectrum imaging and pre-stack azimuthal anisotropy. Identifying the channel sand-bodies in Fuyu oil-layer using the two seismic methods results in a success rate up to 80% compared with well data.

A key aspect in extracting quantitative information from FMI logs is to segment the FMI image to get images of pores, vugs and fractures. A segmentation method based on the dyadic wavelet transform in 2-D is introduced in this paper. The first step is to find all the edge pixels of the FMI image using the 2-D wavelet transform. The second step is to calculate a segmentation threshold based on the average value of the edge pixels. Field data processing examples show that sub-images of vugs and fractures can be correctly separated from original FMI data continuously and automatically along the depth axis. The image segmentation lays the foundation for in-situ parameter calculation.

In an effort to reduce the shale gas exploration risks and costs, we applied the wide-field electromagnetic method (WFEM), because of its strong anti-interference capability, high resolution, ability to conduct exploration at large depths, and high efficiency, to the Bayan Syncline in the South Huayuan block, Hunan Province. We collected rock samples and analyzed their resistivity and induced polarization (IP) and built A series of two-dimensional models for geological conditions to investigate the applicability of WFEM to different geological structures. We also analyzed the correlation between TOC of shale and the resistivity and IP ratio to determine the threshold for identifying target formations. We used WFEM to identify the underground structures and determine the distribution, depth, and thickness of the target strata. Resistivity, IP, and total organic carbon were used to evaluate the shale gas prospects and select favorable areas (sweet spots) for exploration and development. Subsequently, drilling in these areas proved the applicability of WFEM in shale gas exploration.

Receiver ghost reflections adversely affect variable-depth streamer (VDS) data acquisition. In addition, the frequency notches caused by the interference between receiver ghosts and primary waves strongly affect seismic data processing and imaging. We developed a high-resolution Radon transform algorithm and used it to predict receiver ghosts from VDS data. The receiver ghost reflections are subtracted and removed from the raw data. We propose a forward Radon transform operator of VDS data in the frequency domain and, based on the ray paths of the receiver ghosts, we propose an inverse Radon transform operator. We apply the proposed methodology to model and field data with good results. We use matching and subtracting modules of commercially available seismic data processing software to remove the receiver ghosts. The frequency notches are compensated and the effective frequency bandwidth of the seismic data broadens.

The forward modeling procedure used in this article is formulated with the volume integral equation based on the tensor Green’s function. The electromagnetic components responses are first calculated in the frequency domain and then transformed to the time domain by digital filtering. The valley and hill topography with a layered earth is stimulated by a horizontal electric dipole (HED) transmitter, which is common in field surveys, and the TEM responses are calculated at the transmitter and receivers. The topography effects on the long offset electromagnetic transient (LOTEM) responses are discussed in detail. The results show that both valley and hill topography has significant effect on the LOTEM measurement. If the HED is located in the bottom of a valley, the distortion of the observed anomalous field at distance is severe. A valley at the receiver locations show a strong effect but are localized in space and time. In general, hill-shaped topography shows smaller effects no matter where its located. When the topography is located between source and receivers, the influence is negligible. We conclude that the location of the source is much more important than the receivers and it is critical to put the transmitter in an open flat area in the field survey.

The staggered-grid finite-difference (SGFD) method has been widely used in seismic forward modeling. The precision of the forward modeling results directly affects the results of the subsequent seismic inversion and migration. Numerical dispersion is one of the problems in this method. The window function method can reduce dispersion by replacing the finite-difference operators with window operators, obtained by truncating the spatial convolution series of the pseudospectral method. Although the window operators have high precision in the low-wavenumber domain, their precision decreases rapidly in the high-wavenumber domain. We develop a least squares optimization method to enhance the precision of operators obtained by the window function method. We transform the SGFD problem into a least squares problem and find the best solution iteratively. The window operator is chosen as the initial value and the optimized domain is set by the error threshold. The conjugate gradient method is also adopted to increase the stability of the solution. Approximation error analysis and numerical simulation results suggest that the proposed method increases the precision of the window function operators and decreases the numerical dispersion.

When the synthetic aperture focusing technology (SAFT) is used for the detection of the concrete, the signal-to-noise ratio (SNR) and detection depth are not satisfactory. Therefore, the application of SAFT is usually limited. In this paper, we propose an improved SAFT technique for the detection of concrete based on the pulse compression technique used in the Radar domain. The proposed method first transmits a linear frequency modulation (LFM) signal, and then compresses the echo signal using the matched filtering method, after which a compressed signal with a narrower main lobe and higher SNR is obtained. With our improved SAFT, the compressed signals are manipulated in the imaging process and the image contrast is improved. Results show that the SNR is improved and the imaging resolution is guaranteed compared with the conventional short-pulse method. From theoretical and experimental results, we show that the proposed method can suppress noise and improve imaging contrast, and can also be used to detect multiple defects in concrete.

The selection of the truncation level (TL) and the control of boundary effect (BE) are critical in regional geomagnetic field models that are based on data fitting. We combine Taylor and Legendre polynomials to model geomagnetic data over mainland China for years 1960, 1970, 1990, and 2000. To tackle the TL and BE problems, we first determine the range of TL by calculating the root-mean-square error (RMSE) of the models. Next, we determine the optimum TL using the Akaike information criterion (AIC) and the normalized rootmean- square error (NRMSE). We use the regional anomaly addition (RAA) and the uniform addition (UA) method to add supplementary point outside the national boundary, and find that the intensities of extreme points gradually decrease and stabilize. The UA method better controls BEs over China, whereas the RAA method does a better job at smaller scales. In summary, we rely on a three-step method to determine the optimum TL and propose criteria to determine the optimum number of supplementary points.

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.