The application of geostatistics in seismic inversion techniques has been proven somewhat reliable in the delineation of reservoir properties and has recently attracted the attention of many geoscientists. However, there are cases where its prediction returned negative results after drilling. In this research, we re-evaluated a reservoir in Inas Field, whose geostatistical inversion result wrongly predicted sand continuity, resulting in the spudding of a dry hole. When a geostatistical seismic inversion is successfully applied, it provides an increase in seismic resolution and aids the prediction of sand continuity. Although this method relies more on the statistical data from a well because of the limitation of the seismic data in resolving thin geologic features, the spatial variation of reservoir parameters still depends on seismic data, which often have poor resolution quality. Therefore, to investigate the impact of bandlimited data on the geostatistical inversion, we harmonically extended the seismic bandwidth by applying a sparse-layer spectral inversion algorithm to the data. This algorithm increased the seismic data bandwidth from 80 Hz to 180 Hz, and its tuning thickness reduced from 32 m to 10 m at the reservoir interval. The resultant broadband (180 Hz), as well as the original seismic (narrowband of 80 Hz) data, were both used as input to build two separate geostatistical prediction models, respectively. Twenty (20) realizations of these models were generated, ranked into P10, P50, and P90, and the best case was selected for interpretation. These realizations were used to characterize the reservoir lithofacies distribution. When compared, the result of the broadband inversion, facies and sand distribution model showed that the reservoir facies changed towards the location of the dry well. The broadband geostatistical inversion efficiently improved the reservoir characterization process by not only producing an accurate estimation of the lateral extent of the reservoir heterogeneities but also generating outcomes that help us understand why other geostatistical inversion analyses of the target reservoir were misleading. Contrary to the popular assumption, it was discovered that the tuning effects of bandlimited data could affect the result of a geostatistical inversion and result in wrong facies predictions.
For decades, how to improve the resolution limit of seismic data has been a concern for seismologists. For this reason, several geoscientists have proposed various methods of improving the bandwidth of the data. Discovering an easy and scientifically reliable means of improving seismic data resolution would undoubtedly help geophysicists interpret more complex details of the subsurface geology. In this study, we transformed the bandlimited time-domain seismic data to the frequency domain using the Fourier analysis method, and a basis pursuit atomic algorithm was applied to decompose the real and imaginary parts of the spectrum into summations of cosines and sines. The resultant reflectivity spectrum (in the frequency domain) was deconvolved by a pre-estimated wavelet spectrum to obtain the true earth’s reflectivity data spectrum and was subsequently extrapolated to beyond the original band limit. The result shows an extended bandwidth from 68 Hz to 161 Hz and 80 Hz to 170 Hz for both synthetic trace model and the main seismic data, respectively. Consequently, this improved vertical resolution of sub-seismic geologic features, such as crevasse splay, levee, barrier bar complex, lagoon inlet channels, alluvial fans, and fluvial channels, and shows subtle facies variations in Inas field.
Being a fast-growing city with a high rate of urbanization and agricultural development, the city of Najran, situated in the southwest of the Kingdom of Saudi Arabia, has witnessed a series of earth fissuring events and some other geo-environmental hazards in recent times. These fissures have posed a significant threat to inhabitants and infrastructure in the area. A few studies suggest that excessive groundwater withdrawal is responsible for fissuring activities. Because of the intensity of this geo-hazard, this article presupposes that groundwater extraction alone cannot be responsible for the magnitude of fissuring activity in the area and discusses other severe factors that could be responsible for the earth fissures. The study proposes that the cause of the problem is multifaceted and synergistic, and outlines threatening factors that can inherently trigger more fissures in the region, based on the geologic history of the area and a critical review of investigative studies conducted in the area and beyond. Predicated on the region’s structural history, some undiscovered elements that can potentially cause fissuring in the region were identified and discussed. Some of these include the pre-existence of a fault system, a crack from the bedrock ridge, the existence of paleochannels, the collapsibility of loess, the tectonic (earthquake) history of the area, and differential compaction due to heterogeneity. The use of a metaheuristic and a combined application integrating other optimization algorithms can be utilized to determine optimum hyperparameters and present their statistical importance, thereby improving accuracy and dependability in fissure prediction in Najran. Reliable models would primarily be used to monitor active fissures and identify key factors utilizing spatial information, subsidence, groundwater-related data sets, etc.
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