Seismic edge detection algorithm unmasks blurred discontinuity in an image and its efficiency is dependent on the precession of the processing scheme adopted. Data-driven modeling is a ast machine learning scheme and a formal usually automatic version of the empirical approach in existence for long time and which can be used in many different contexts. Here, a desired algorithm that can identify masked connection and correlation from a set of observations is built and used.Geologic models of hydrocarbon reservoirs facilitate enhanced visualization, volumetric calculation, well planning and prediction of migration path for fluid. In order to obtain new insights and test the mappability of a geologic feature, spectral decomposition techniques i.e. Discrete Fourier Transform (DFT), etc and Cepstral decomposition techniques, i.e Complex Cepstral Transform (CCT), etc can be employed. Cepstral decomposition is a new approach that extends the widely used process of spectral decomposition which is rigorous when analyzing very subtle stratigraphic plays and fractured reservoirs. This paper presents the results of the application of DFT and CCT to a two dimensional, 50Hz low impedance Channel sand model, representing typical geologic environment around a prospective hydrocarbon zone largely trapped in various types of channel structures. While the DFT represents the frequency and phase spectra of a signal, assumes stationarity and highlights the average properties of its dominant portion, assuming analytical, the CCT represents the quefrency and saphe cepstra of a signal in quefrency domain. The transform filters the field data recorded in time domain, and recovers lost sub-seismic geologic information in quefrency domain by separating source and transmission path effects. Our algorithm is based on fast Fourier transform (FFT) techniques and the programming code was written within Matlab software. It was developed from first principles and outside oil industry’s interpretational platform using standard processing routines. The results of the algorithm, when implemented on both commercial and general platforms, were comparable. The cepstral properties of the channel model indicate that cepstral attributes can be utilized as powerful tool in exploration problems to enhance visualization of small scale anomalies and obtain reliable estimates of wavelet and stratigraphic parameters. The practical relevance of this investigation is illustrated by means of sample results of spectral and cepstral attribute plots and pseudo-sections of phase and saphe constructed from the model data. The cepstral attributes reveal more details in terms of quefrency required for clearer imaging and better interpretation of subtle edges/discontinuities, sand–shale interbedding, differences in lithology. These positively impact on production as they serve as basis for the interpretation of similar geologic situations in field data.
Velocity analysis was conducted in, Agbada Field, onshore Niger Delta using geostatistical tools. This provided a quantitative technique of integrating interval velocities from Checkshots and Sonic Logs for 60 wells with the two-way travel time from 3-D pre-stacked seismic image data for an identified reservoir (D5.2). Analyses by crossplots, regression plot with variogram modelling, and kriging produced results useful in improving on some of the associated limitations arising from spatial data continuity, anisotropy and azimuthal properties inherent in velocity data. Besides, error term analysis, poor correlation between primary and secondary data, and improper calibration of data from various sources result in poor depth estimate. Geostatistical velocity analysis facilitates enhanced estimation and better depth conversion. This will improve the existing structural framework necessary for the quantification of bypassed hydrocarbon and possible redevelopment of the fields in the Niger Delta, Nigeria.
The aim of this study is to introduce a novel technique used for mapping subsurface structures in a sedimentary environment using the magnetic exploration method. Vertical component of the Earth’s magnetic field and its derivative taken at 1.4m above the measured vertical field were acquired in parts of Federal University of Petroleum Resources Effurun, Delta State, using an AMC-6 high precision magnetometer. The datasets were analysed by logarithmic curves. Six magnetic profiles were established in the area five in the strike direction and one along dip lines. A total of ten stations were sampled along each profile with an interstation spacing of 2m. This was followed by the conversion of the vertical field into geomagnetic attributes after the necessary corrections were applied to the data. The data was plotted in logarithm to base two to show the pattern of distribution of the data since the normal plot does not show the distribution clearly as datasets show feeble changes and the readings were close in amplitude values. When datasets are closed we check for the skewness of the data. The result obtained showed regions of high data concentration which corresponds to a peak (highest point) on the logarithmic plot and indicates anomalous zones of interest within the subsurface. Map of vertical components of the area showed steep slope (closely spaced contours) observed towards the North-Eastern part of the area while at the central part, anticlinal structures which decrease gentle outwardly were observed and a gentle slope which decreases towards the west was also observed. The result indicates the presence of anticlinal structures in the subsurface which have valley-like depressions between them
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