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Cui S.-L.,CAS Guangzhou Institute of Geochemistry | Cui S.-L.,Geophysical Prospecting Research Institute of Shengli Oilfield | Zhang J.-H.,China University of Petroleum - East China | Wang W.,Research Institute of BGP
Wutan Huatan Jisuan Jishu | Year: 2010

Texture analysis is a common technology in image processing, which can be extended to the field of geophysical prospecting by constructing seismic texture primitive and gray level co-occurrence matrix. It can be used in fault identification, edge detection and sedimentary facies delineation. Through the algorithm research, programming and practical application, we get some conclusions which has theoretical meaning and valuable (1)The texture attribute which based on gray level co-occurrence matrix is a good attribute in highlighting the information of faults and fractures, (2) According to actual geological problems, we can extract texture attributes of different directions, and use RGB technology for the integration of multi-attributes, (3)The window of seismic texture element we should adopt is 9 × 9 × 9, (4) We should select a reasonable level of gray of different conditions, and commonly selection is 16 or 32 for conventional diree-dimensional seismic data.


Wu M.,Geoscience Research Institute of Shengli Oilfield | Wu M.,Tongji University | Lu S.-Q.,Geophysical Prospecting Research Institute of Shengli Oilfield | Yang F.-L.,Tongji University
Wutan Huatan Jisuan Jishu | Year: 2012

Several sets of fan-delta develop in the forth member of shahejie formation, in Luojia area, Jiyang depression. It has been conformed by well and core data that the effective reservoirs usually consist in the micro-facies of subaqueous distributary channel in sub-facies of fan-dalta front. However, structural complexity and rapid lateral changes of reservoirs and low seismic resolution have been restricted the facies precise identification in conventional wave-impedance inversion seismic data. Therefore, high-density seismic data is used and the reconstructed-logs pseudo-wave impedance seismic inversion is adopted in this paper. These attempts increase the facies seismic i- dentification accuracy to micro-facies, obtaining sound effects.


Zhang J.,China University of Petroleum - East China | Wangwei,Research Institute of BGP | Tan M.,Geophysical Prospecting Research Institute of Shengli Oilfield | Cui S.L.,Geophysical Prospecting Research Institute of Shengli Oilfield | Chen H.,Geophysical Prospecting Research Institute of Shengli Oilfield
Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010 | Year: 2010

Curvature attribute interpretation is a new interpretation technology rising in the recent two years. Curvature attributes provide images of structure and stratigraphy that complement those seen by the well accepted coherence algorithms. The article expounds the definition of the curvature, the physical meaning and its shortages in structural interpretation from the most basic mathematical definition. On this basis, we describe 2D curvature of the surface, list and compare the definition, physical meaning and its main usages of surface-derived attributes. After interpolation and 2D median filtering of t0 contour data, we extract 8 attributes with fractional-order method including mean curvature, Gaussian curvature, maximum curvature, minimum curvature, most positive curvature, most negative curvature, dip curvature, and strike curvature. Finally, we apply most positive curvature to detect fault and fracture and achieve better results. © 2010 IEEE.


Yang C.,China University of Petroleum - East China | Zhang J.,China University of Petroleum - East China | Meng X.,Geophysical Prospecting Research Institute of Shengli Oilfield | Wang L.,Geophysical Prospecting Research Institute of Shengli Oilfield | Lv X.,Geophysical Prospecting Research Institute of Shengli Oilfield
Proceedings - 2010 2nd International Workshop on Intelligent Systems and Applications, ISA 2010 | Year: 2010

The hyperbolic approximation of P-wave reflection traveltimes in common-midpoint gathers plays an important role in conventional seismic data processing and interpretation. It is well known that the normal moveout formula is based upon homogeneous isotropic media. The familiar hyperbolic approximation of P-wave reflection moveout is exact for homogeneous isotropic or elliptically anisotropic media above a planar reflector. Any realistic combination of heterogeneity, anisotropic coefficient, and nonelliptic anisotropy will cause departures from hyperbolic moveout at large offsets. Therefore, nonhyperbolic moveout gives exact traveltimes for elliptically anisotropic media overlaying a plane dipping reflector. In this paper, we compare a theoretical description of P-wave reflection traveltimes and degree of nonhyperbolic moveout with different anisotropic parameters. ©2010 IEEE.


Zhang J.,China University of Petroleum - East China | Zang S.,China University of Petroleum - East China | Shan L.,Geophysical Prospecting Research Institute of Shengli Oilfield | Shi L.,Geophysical Prospecting Research Institute of Shengli Oilfield | Liang F.,Geophysical Prospecting Research Institute of Shengli Oilfield
Proceedings - 2010 2nd International Workshop on Intelligent Systems and Applications, ISA 2010 | Year: 2010

The surface wave has serious impact on the effective reflections due to its extensive existence, strong power, and wide frequency band. Here described is surface wave attenuation using frequency division of wavelet transform and radial trace transform (RRT). Wavelet frequency division decomposes seismic profile into several different frequency sections by changing seismic data of temporal spatial domain into wavelet domain, we can eliminate surface wave applying purposeful processing. The radial trace transform is a simple seismic data mapping algorithm, which differs effective wave and noise in frequency by changing coordinate system, and then remove the noise using highpass filtering. Here we made use of the advantages of the two methods in model test and field data, and got a wonderful result. ©2010 IEEE.


Wang J.,China University of Petroleum - East China | Zhang J.-H.,China University of Petroleum - East China | Shan J.-Y.,Geophysical Prospecting Research Institute of Shengli Oilfield
Wutan Huatan Jisuan Jishu | Year: 2010

In this paper, we calculate stack velocity spectrum using instantaneous phase correlation characteristic of seismic signal and statistical hypothetical test principle in probability method. We conduct test and calculation using synthetic and real data and compare with conventional velocity spectrum. The results showed that the method has higher resolution in velocity and in time and has better anti - noise property compared with conventional methods. This method, which does not suffer from time - window boundary singularity, can avoid edge effects and give much more reflection information. This method is taken as the key to calculate interval velocity and the result indicates that using statistical method in multi - channel signal estimation is also effective.


Zhang J.,China University of Petroleum - East China | Wang J.,China University of Petroleum - East China | Liang X.,China University of Petroleum - East China | Liu Z.,China University of Petroleum - East China | And 3 more authors.
Acta Seismologica Sinica | Year: 2011

The detection and identification of weak signal is a well-known technical issue in today's geophysical industry. For high-density single sensor data, there is little information on how weak the signal will be called weak signal and how to detect and identify it in existing academic literatures. Based on theoretical study and combined with analyzing LJ high density data from Shengli Oil-field these questions were touched with and discussed in this paper. We draw the following conclusions; (T) In terms of visual resolution, the weak signal is more easily identified when signal to noise ratio S/N>2, it may be wrongly identified when S/N=1, and it is basically impossible by visual recognition and interpretation when S/N<0.5. (2) For thin reservoir, S/N=2 is the lower limit for estimating its thickness. (3) Background noise will significantly affect the weak signals in deep part and the death value of high-density data weak signal is just the amplitude of environmental noise. (4) A single weak signal shares less in the frequency spectrum. Random noise mainly affects high frequency and low frequency part of the spectrum, and the spectrum response is remarkably altered even if S/N comes up to 5. (5) High-density data has a wide frequency band of 5-210 Hz. Target layer has faster high-frequency attenuation and the death value of high frequency is at 170 Hz. The signal above 20 Hz in deep layer shows similar variation with the noise and the weak signal is difficult to be detected. (6) Horizontal co-phase weak signal mixed with noise (S/N>1) can still be effectively detected after processed with singular value decomposition (SVD), and the S/N = 0.5 is the cut-off point determining whether SVD can be used to process the common midpoint (CMP) data after normal moveout (NMO) or not. Even if N/S reaches to 3, it can still be restored by curvelet transform. This gives us an enlightenment that, for high-density single-point data, there is still large potential of identifying more weak signals as long as we use a proper processing technique.


Zhang J.-H.,China University of Petroleum - East China | Zhang B.-B.,China University of Petroleum - East China | Zhang Z.-J.,China University of Petroleum - East China | Liang H.-X.,Geophysical Prospecting Research Institute of Shengli Oilfield | Ge D.-M.,Geophysical Prospecting Research Institute of Shengli Oilfield
Applied Geophysics | Year: 2015

The use of low-frequency seismic data improves the seismic resolution, and the imaging and inversion quality. Furthermore, low-frequency data are applied in hydrocarbon exploration; thus, we need to better use low-frequency data. In seismic wavelets, the loss of low-frequency data decreases the main lobe amplitude and increases the first side lobe amplitude and results in the periodic shocking attenuation of the secondary side lobe. The loss of low frequencies likely produces pseudo-events and the false appearance of higher resolution. We use models to examine the removal of low-frequency data in seismic data processing. The results suggest that the removal of low frequencies create distortions, especially for steep structures and thin layers. We also perform low-frequency expansion using compressed sensing and sparse constraints and develop the corresponding module. Finally, we apply the proposed method to real common image point gathers with good results. © 2015, Editorial Office of Applied Geophysics and Springer-Verlag Berlin Heidelberg.

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