Sequence stratigraphic analysis of Eocene Rock Strata,Offshore Indus,southwest Pakistan

In this study, seismic data from two wells (Pak G2-1 and Indus Marine-1C) and age diagnostic larger benthic foraminifera (LBF) within drill cuttings has been used for the first time to identify depositional sequences within the carbonates in the Offshore Indus Basin, Pakistan. The Offshore Indus is tectonically categorized as a passive continental margin where carbonates occur as shelf carbonates in the near offshore and on volcanic seamounts in deeper waters. Seismic data analysis has indicated the presence of minor faults and carbonate buildups above the igneous basement in the south. Patterns of the seismic reflections enabled definition of three seismic facies units identified as: Unit 1 basement, represented by chaotic, moderate amplitude reflection configuration; while parallel bedding and the drape of overlying strata is typical character of Unit 2, carbonate mound facies. The younger Miocene channels represent Unit 3. The diagnosis of Alveolina vredenburgi/cucumiformis biozone confirmed the Ilerdian (55–52 Ma) stage constituting a second order cycle of deposition for the Eocene carbonates (identified as Unit 2). The carbonate succession has been mainly attributed to an early highstand system tract (HST). The environmental conditions remained favorable leading to the development of keep-up carbonates similar to pinnacle buildups as a result of aggradation during late transgressive system tract and an early HST. The carbonate sequence in the south (Pak G2-1) is thicker and fossiliferous representing inner to middle shelf depths based on fauna compared to the Indus Marine-1C in the north, which is devoid of fossils. Three biozones (SBZ 5, SBZ 6 and SBZ 8) were identified based on the occurrence of LBF. The base of the SBZ 5 zone marks the larger foraminifera turnover and the Paleocene–Eocene (P–E) boundary. The LBF encountered in this study coincides with earlier findings for the P–E boundary. Our findings indicate that the entire Ilerdian stage ranges from 55.5 to 52 Ma that was the episode of warmer water conditions on the carbonate shelves leading to the diversification of K-strategist larger foraminifera. The larger foraminiferal assemblage encountered in this study confirms the findings. The possible indication of stratigraphic-combination traps, revealed as reflection terminations, make carbonate mounds in the south a potential exploration target.     

Practical Incorporation of Multivariate Parameter Uncertainty in Geostatistical Resource Modeling

There is a need to bridge theory and practice for incorporating parameter uncertainty in geostatistical simulation modeling workflows. Simulation workflows are a standard practice in natural resource and recovery modeling, but the incorporation of multivariate parameter uncertainty into those workflows is challenging. However, the objectives can be met without considerable extra effort and programming. The sampling distributions of statistics comprise the core theoretical notion with the addition of the spatial degrees of freedom to account for the redundancy in the spatially correlated data. Prior parameter uncertainty is estimated from multivariate spatial resampling. Simulation-based transfer of prior parameter uncertainty results in posterior distributions which are updated by data conditioning and the model domain extents and configuration. The results are theoretically tractable and practical to achieve, providing realistic assessments of uncertainty by accounting for large-scale parameter uncertainty, which is often the most important component impacting a project. A simulation-based multivariate workflow demonstrates joint modeling of intrinsic shale properties and uncertainty in estimated ultimate recovery in a shale gas project. The multivariate workflow accounts for joint prior parameter uncertainty given the current well locations and results in posterior estimates on global distributions of all modeled properties. This is achieved by transferring the joint prior parameter uncertainty through conditional simulations.     

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Blasting is a widely used technique for rock fragmentation in opencast mines and tunneling projects. Ground vibration is one of the most environmental effects produced by blasting operation. Therefore, the proper prediction of blast-induced ground vibrations is essential to identify safety area of blasting. This paper presents a predictive model based on gene expression programming (GEP) for estimating ground vibration produced by blasting operations conducted in a granite quarry, Malaysia. To achieve this aim, a total number of 102 blasting operations were investigated and relevant blasting parameters were measured. Furthermore, the most influential parameters on ground vibration, i.e., burden-to-spacing ratio, hole depth, stemming, powder factor, maximum charge per delay, and the distance from the blast face were considered and utilized to construct the GEP model. In order to show the capability of GEP model in estimating ground vibration, nonlinear multiple regression (NLMR) technique was also performed using the same datasets. The results demonstrated that the proposed model is able to predict blast-induced ground vibration more accurately than other developed technique. Coefficient of determination values of 0.914 and 0.874 for training and testing datasets of GEP model, respectively show superiority of this model in predicting ground vibration, while these values were obtained as 0.829 and 0.790 for NLMR model.     

Reflectance spectroscopy and remote sensing data for finding sulfide-bearing alteration zones and mapping geology in Gilgit-Baltistan,Pakistan

Gilgit-Baltistan region is covering the northern most part of Pakistan where the rocks of the Kohistan-Ladakh island arc and Karakoram plate are exposed. The area has greater potential for precious and base metals deposits which are needed to be explored through spectroscopy and remote sensing techniques. Minerals and rocks can nowadays be identified through the measurement of their absorption and reflectance features by spectroscopic analysis. Spectral reflectance analysis is also very important in selecting the appropriate spectral bands for remote-sensing data analysis of unknown or inaccessible areas. In this study, reflectance spectra in the spectral range of 0.35–2.5 μm of different types of unaltered and altered rocks found in the Machulu and Astor areas of northern Pakistan were obtained using an ASD spectroradiometer. The fresh rock samples showed low spectral reflectance as compared to the altered rock samples. The minerals jarosite, goethite, and hematite showed depth of absorption minima in the range of 0.4–1.15 μm due to the presence of iron (Fe), while jarosite and limonite showed absorption depth at 2.2 μm due to the presence of hydroxyl ions (OH^¯). The clay minerals montmorillonite and illite showed absorption depth at 1.93 and 2.1 μm, respectively. Muscovite showed depth of absorption minima at 1.4 and 1.9 μm in some samples. Calcite showed deep absorption minima at 2.32 μm, while anorthite showed absorption features at 1.4, 1.9, 2.24, and 2.33 μm. Olivine showed a slight depressed absorption feature at 1.07 μm. The copper-bearing phases malachite, chrysocolla, and azurite showed, respectively, a broad absorption feature in the range of 0.6–0.9 μm, a small absorption at 1.4 μm, and a deep absorption at 1.93 μm. The unmineralized samples exhibited high reflectance in the wavelength ranges of 0.6–0.8, 1.6–1.9, 2.0–2.3, 2.1–2.25, and 2.4–2.5 μm, respectively, while the mineralized samples showed reflectance bands in the wavelength ranges of 0.4–0.6, 1.3–1.8, and 2.1–2.2 μm. On this basis, the band ratio combinations 7/5–4/3–6/3 and 7/5–6/3–4/3 of Landsat 8 and 4/7–4/3–2/1 for ASTER data were found to be very effective in the lithological differentiation of major rock units.     

A spatio-temporal three-dimensional conceptualization and simulation of Dera Ismail Khan alluvial aquifer in visual MODFLOW: a case study from Pakistan

Dera Ismail Khan (DIK) is situated in the Lower Indus Basin of Pakistan. The land use has been changed in the canal command area due to irrigation activities near the Indus River. To check the current status and predict the groundwater levels in the area, the unconfined aquifer has been simulated in Visual MODFLOW for a period of 35 years, i.e., from 1985 to 2020. The 2900-km² area has been modeled with a grid of 500 by 500 m and the depth set to 100 m. The aquifer in the study area has been divided vertically and laterally into three and ten zones, respectively, for the characterization. Water wells and streams were used as the sinks and hydrologic boundaries, respectively. The model was successfully calibrated in steady and the non-steady state. The simulation revealed that the whole simulation can be divided into two phases, i.e., before and after the construction of the Chashma Right Bank Canal (CRBC), whereas the results were summarized in the form of water table depth maps and groundwater budget calculations. To determine the groundwater sustainability, a conjunctive use scenario has been employed to simulate the aquifer dynamics till 2020. The simulation revealed incremental drawdowns till the end.