• Economic and Environmental Geology
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• v.57 no.1
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• pp.51-71
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• 2024

Seismic exploration is one of the widely used geophysical exploration methods with various applications such as resource development, geotechnical investigation, and subsurface monitoring. It is essential for interpreting the geological characteristics of subsurface by providing accurate images of stratum structures. Typically, geological features are interpreted by visually analyzing seismic sections. However, recently, quantitative analysis of seismic data has been extensively researched to accurately extract and interpret target geological features. Seismic attribute analysis can provide quantitative information for geological interpretation based on seismic data. Therefore, it is widely used in various fields, including the analysis of oil and gas reservoirs, investigation of fault and fracture, and assessment of shallow gas distributions. However, seismic attribute analysis is sensitive to noise within the seismic data, thus additional noise attenuation is required to enhance the accuracy of the seismic attribute analysis. In this study, four kinds of seismic noise attenuation methods are applied and compared to mitigate random noise of poststack seismic data and enhance the attribute analysis results. FX deconvolution, DSMF, Noise2Noise, and DnCNN are applied to the Youngil Bay high-resolution seismic data to remove seismic random noise. Energy, sweetness, and similarity attributes are calculated from noise-removed seismic data. Subsequently, the characteristics of each noise attenuation method, noise removal results, and seismic attribute analysis results are qualitatively and quantitatively analyzed. Based on the advantages and disadvantages of each noise attenuation method and the characteristics of each seismic attribute analysis, we propose a suitable noise attenuation method to improve the result of seismic attribute analysis.

• Geophysics and Geophysical Exploration
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• v.2 no.3
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• pp.149-153
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• 1999

The study was performed as a part of 3-D exploration project of the South Con Son basin, where Korea National Oil Co. (KNOC) and SHELL Company are performing joint operation. In the structurally complex area, seismic facies or lap-out patterns, which are usually the tools for the conventional seismic stratigraphy developed by Exxon Group (Vail et at., 1977), are not easily identifiable. Therefore, stratigraphic informations are mainly extracted from seismic attribute maps of each sequence or systems tracts, and isopach maps in correlation with the stratigraphic information from the wells. The attribute maps of the sequence or systems tract boundaries and isopach map describe the variations of paleodepositional environments. The shape of the attribute maps of the boundaries is a reasonable description of the shape of the paleodepositional surface. With other maps such as isopach and structural maps, the variations of the parasequences in the systems tracts can be projected using the surface attribute maps. The reflection intensity attribute at each sequence or system tract boundary can be related to lithology, facies or porosity distributions. The azimuth attribute of source rock sequence can be used to identify the hydrocarbon migration patterns into the prospects. The overall risks of reservoir rocks, cap rocks, structure and hydrocarbon migrations were computed using the results of the study.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.208-212
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• 2008

Gas hydrate has been paid attention to study for because: 1) it can be considered as a new energy resources; 2) one of reasons causing the instability of sea floor slope and 3) a factor to the climate change. Bottom simulating reflector (BSR) defined as seismic boundary between the gas hydrate and free gas zone has been considered as the most common evidence in the seismic reflection data for the gas hydrate exploration. BSR has several characteristics such as parallel to the sea bottom, high amplitude, reducing interval velocity between above and below BSR and reversing phase to the sea bottom. Moreover, instantaneous attribute properties such as amplitude envelop, instantaneous frequency, phase and first derivative of amplitude of seismic data from the complex analysis could be used to analyze properties of BSR those would be added to the certain properties of BSR in order to effectively find out the existence of BSR of the gas hydrate stability zone. The output of conventional seismic data processing for gas hydrate data set in Ulleung basin in the East sea of Korea will be used for complex analyses to indicate better BSR in the seismic reflection data. This result of this analysis implies that the BSR of the analyzed seismic profile is clearly located at the two ways time (TWT) of around 3.1 seconds.

• Geophysics and Geophysical Exploration
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• v.17 no.4
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• pp.216-230
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• 2014

Based on the interpretation of 3D seismic profiles acquired in the northwestern area of the Ulleung Basin, East Sea, the shallow sediments consist of five seismic units separated by regional reflectors. An anticline is present in the study area that documents activity of many faults. Bottom simulating reflectors are characterized by high RMS amplitude. Acoustic blanking with low RMS amplitude is distinctively recognized in the gas hydrate stability zone. Seismic attribute analysis shows that if gas hydrates are underlain by free gas, the high reflection strength and the low instantaneous frequency are displayed below the boundary between them. Whereas, if not, the reflection strength is low and instantaneous frequency is high continuously below the gas hydrate zone. Based on the spectral decomposition of the bottom simulating reflector, the high envelope at the specific high frequency range indicates the generation of the tuning effect due to the lower free gas content. Four models for the occurrence of the gas hydrate are suggested considering the slope of sedimentary layers as well as the presence of gas hydrate or free gas.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.723-730
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• 2003

In general, well log and core data have been utilized for reservoir characterization. These well data can provide valuable information on reservoir properties with high vertical resolution at well locations. While the seismic surveys cover large areas of field but give only indirect features about reservoir properties. Therefore it is possible to estimate the reservoir properties guided by seismic data on entire area if a relationship of seismic data and well data can be defined. Seismic attributes calculated from seismic surveys contain the particular reservoir features, so that they should be extracted and used properly according to the purpose of study. The method to select the suitable seismic attributes among enormous ones is needed. The stepwise regression and fuzzy curve analysis based on fuzzy logics are used for selecting the best attributes. The relationship can be utilized to estimate reservoir properties derived from seismic attributes. This methodology is applied to a synthetic seismogram and a sonic log acquired from velocity model. Seismic attributes calculated from the seismic data are reflection strength, instantaneous phase, instantaneous frequency and pseudo sonic logging data as well as seismic trace. The fuzzy curve analysis is used for choosing the best seismic attributes compared to sonic log as well data, so that seismic trace, reflection strength, instantaneous frequency, and pseudo sonic logging data are selected. The relationship between the seismic attribute and well data is found out by the statistical regression method and estimates the reliable well data at a specific field location derived from only seismic attributes. For a future work in this study, the methodology should be checked an applicability of the real fields with more complex and various reservoir features.

• Geophysics and Geophysical Exploration
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• v.16 no.3
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• pp.163-170
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• 2013

The amplitude variation with offset of seismic data can detect fluids in the sediment and resolve the petrophysical properties of hydrocarbons in the subsurface. We analyzed and described the amplitude variation in deep sea seismic data obtained from the Ulleung Basin, East Sea. By inspecting seismic CDP-offset and CDP-angle gathers which show a bright reflection event, we decided a target zone for amplitude variation analysis. From the seismic angle gather at the middle of Ulleung Basin, we recognized amplitude increase or decrease versus offset on the intercept-gradient curve. Using the product attribute and Poisson's ratio change attribute computed in terms of intercept with gradient, the top and the base of gas saturated sediments were described. The area of amplitude variation suggestive of the presence of gas saturated sediments is shown at the depth of 3 s traveltime. Anomalous features of seismic amplitude in the Ulleung Basin were classified by the crossplot of intercept and gradient. The background trend of crossplot between intercept and gradient shows an inverse proportional relation that is common for wet sediments. Anomalous amplitudes of Class III fall into the first and the third quadrants on crossplots. We inferred regional gas/water saturated area with the horizontal dimension of 150 m in the Ulleung Basin by cross-section with respect to cross-plot anomaly.

• Geophysics and Geophysical Exploration
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• v.23 no.2
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• pp.97-114
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• 2020

Recently, many studies have been actively conducted on the application of machine learning in all branches of science and engineering. Studies applying machine learning are also rapidly increasing in all sectors of seismic exploration, including interpretation, processing, and acquisition. Among them, fault detection is a critical technology in seismic interpretation and also the most suitable area for applying machine learning. In this study, we introduced various machine learning techniques, described techniques suitable for fault detection, and discussed the reasons for their suitability. We collected papers published in renowned international journals and abstracts presented at international conferences, summarized the current status of the research by year and field, and intensively analyzed studies on fault detection using machine learning. Based on the type of input data and machine learning model, fault detection techniques were divided into seismic attribute-, image-, and raw data-based technologies; their pros and cons were also discussed.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.103-106
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• 2000

Geophysical data sets from the Chojeong area in the Chungbuk-Do are compositely studied in terms of multi-attribute interpretation for the subsurface mapping of shallow fracture zones, associated with groundwater reservoir. Utilizing a GIS software, the attribute data are implemented to a database; a lineament from the satellite image, electrical resistivities and its standard deviation, radioactivity, seismic velocity, bedrock depth from exploration data. In an attempt to interpret 1-D electrical sounding data in 2-D and 3-D views, 2-D resistivities structures are firstly made by interpolating 1-D plots. Reconstruction of a resistivity volume is found to be an effective scheme for subsurface mapping of shallow fracture zones. Shallow fracture zones in the southeastern part of the study area are commonly correlated in the various exploration data.

• Economic and Environmental Geology
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• v.47 no.6
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• pp.673-681
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• 2014

Recently, many countries in the world try to develop alternative energy sources, however, traditional hydrocarbon resources are still occupying most of the energy resources. Exploration demands for high technologies are increasing in the development of limited oil & gas resources field owing to the exhaustion of hydrocarbon resources for access area. Therefore, an effort for the development and the application of new technologies such as azimuth seismic survey, ocean-bottom seismic survey and marine controlled-source electromagnetic survey is necessary as well as an understanding of the existing technologies such as 2D/3D seismic survey. This dissertation is designed with the purpose of introducing marine hydrocarbon exploration technologies and analyzing their internalexternal researches, development and science information. In this study, we analised total 616 dissertations for the marine petroleum exploration released in the Sci-expanded DB of 'web of science' during the 2001~2014 periods.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.665-673
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• 2011

In order to estimate the hydrocarbon reserves, the porosity of the reservoir must be determined. The porosity of the area without a well is generally calculated by extrapolating the porosity logs measured at wells. However, if not only well logs but also seismic data exist on the same site, the more accurate pseudo porosity log can be obtained through artificial neural network technique by extracting the relations between the seismic data and well logs at the site. In this study, we have developed a module which creates pseudo porosity logs by using the polynomial neural network method. In order to obtain more accurate pseudo porosity logs, we selected the seismic attributes which have high correlation values in the correlation analysis between the seismic attributes and the porosity logs. Through the training procedure between selected seismic attributes and well logs, our module produces the correlation weights which can be used to generate the pseudo porosity log in the well free area. To verify the reliability and the applicability of the developed module, we have applied the module to the field data acquired from F3 Block in the North Sea and compared the results to those from the probabilistic neural network method in a commercial program. We could confirm the reliability of our module because both results showed similar trend. Moreover, since the pseudo porosity logs from polynomial neural network method are closer to the true porosity logs at the wells than those from probabilistic method, we concluded that the polynomial neural network method is effective for the data sets with insufficient wells such as F3 Block in the North Sea.