The precise characterization of reservoir parameters is vital for future development and prospect evaluation of oil and gas fields. C-sand and B-sand intervals of the Lower Goru Formation (LGF) within the Lower Indus Basin (LIB) are proven reservoirs. Conventional seismic amplitude interpretation fails to delineate the heterogeneity of the sand-shale facies distribution due to limited seismic resolution in the Sawan gas field (SGF). The high heterogeneity and low resolution make it challenging to characterize the reservoir thickness, reservoir porosity, and the factors controlling the heterogeneity. Constrained sparse spike inversion (CSSI) is employed using 3D seismic and well log data to characterize and discriminate the lithofacies, impedance, porosity, and thickness (sand-ratio) of the C- and B-sand intervals of the LGF. The achieved results disclose that the CSSI delineated the extent of lithofacies, heterogeneity, and precise characterization of reservoir parameters within the zone of interest (ZOI). The sand facies of C- and B-sand intervals are characterized by low acoustic impedance (AI) values (8 × 10⁶ kg/m²s to 1 × 10⁷ kg/m²s), maximum sand-ratio (0.6 to 0.9), and maximum porosity (10% to 24%). The primary reservoir (C-sand) has an excellent ability to produce the maximum yield of gas due to low AI (8 × 10⁶ kg/m²s), maximum reservoir thickness (0.9), and porosity (24%). However, the secondary reservoir (B-sand) also has a good capacity for gas production due to low AI (1 × 10⁷ kg/m²s), decent sand-ratio (0.6), and average porosity (14%), if properly evaluated. The time-slices of porosity and sand-ratio maps have revealed the location of low-impedance, maximum porosity, and maximum sand-ratio that can be exploited for future drillings. Rock physics analysis using AI through inverse and direct relationships successfully discriminated against the heterogeneity between the sand facies and shale facies. In the corollary, we proposed that pre-conditioning through comprehensive petrophysical, inversion, and rock physics analysis are imperative tools to calibrate the factors controlling the reservoir heterogeneity and for better reservoir quality measurement in the fluvial shallow-marine deltaic basins.

The identification of small scale faults (SSFs) and fractures provides an improved understanding of geologic structural features and can be exploited for future drilling prospects. Conventional SSF and fracture characterization are challenging and time-consuming. Thus, the current study was conducted with the following aims: (a) to provide an effective way of utilizing the seismic data in the absence of image logs and cores for characterizing SSFs and fractures; (b) to present an unconventional way of data conditioning using geostatistical and structural filtering; (c) to provide an advanced workflow through multi-attributes, neural networks, and ant-colony optimization (ACO) for the recognition of fracture networks; and (d) to identify the fault and fracture orientation parameters within the study area. Initially, a steering cube was generated, and a dip-steered median filter (DSMF), a dip-steered diffusion filter (DSDF), and a fault enhancement filter (FEF) were applied to sharpen the discontinuities. Multiple structural attributes were applied and shortlisted, including dip and curvature attributes, filtered and unfiltered similarity attributes, thinned fault likelihood (TFL), fracture density, and fracture proximity. These shortlisted attributes were computed through unsupervised vector quantization (UVQ) neural networks. The results of the UVQ revealed the orientations, locations, and extensions of fractures in the study area. The ACO proved helpful in identifying the fracture parameters such as fracture length, dip angle, azimuth, and surface area. The adopted workflow also revealed a small scale fault which had an NNW–SSE orientation with minor heave and throw. The implemented workflow of structural interpretation is helpful for the field development of the study area and can be applied worldwide in carbonate, sand, coal, and shale gas fields.

Changing ecological communities in response to anthropogenic activities and climate change has become a worldwide problem. The eutrophication of waterbodies in freshwater and seawater caused by the effects of human activities and nutrient inputs could result in harmful algae blooms (HABs), decreases water quality, reductions in biodiversity and threats to human health. Rapid and accurate monitoring and assessment of aquatic ecosystems are imperative. Environmental DNA (eDNA) analysis using high-throughput sequencing has been demonstrated to be an effective and sensitive assay for detecting and monitoring single or multiple species in different samples. In this study, we review the potential applications of eDNA approaches in controlling and mitigating eutrophication and HABs in freshwater and marine ecosystems. We use recent studies to highlight how eDNA methods have been shown to be a useful tool for providing comprehensive data in studies of eutrophic freshwater and marine environments. We also provide perspectives on using eDNA techniques to reveal molecular mechanisms in biological processes and mitigate eutrophication and HABs in aquatic ecosystems. Finally, we discuss the feasible applications of eDNA for monitoring biodiversity, surveying species communities and providing instructions for the conservation and management of the environment by integration with traditional methods and other advanced techniques.

The tight gas reserves in the Hangjinqi area are estimated at 700 × 109 m³. Since the exploration of the Hangjinqi, numerous wells are already drilled. However, the Hangjinqi remains an exploration area and has yet to become a gas field. Identifying a paleo-depositional framework such as braided channels is beneficial for exploration and production companies. Further, braided channels pose drilling risks and must be properly identified prior to drilling. Henceforth, based on the significance of paleochannels, this study is focused on addressing the depositional framework and sedimentary facies of the first member (P²x¹) of the lower Shihezi formation (LSF) for reservoir quality prediction. Geological modeling, seismic attributes, and petrophysical modeling using cores, logs, interval velocities, and 3D seismic data are employed. Geological modeling is conducted through structural maps, thickness map, and sand-ratio map, which show that the northeastern region is uplifted compared to northwestern and southern regions. The sand-ratio map showed that sand is accumulated in most of the regions within member-1. Interval velocities are incorporated to calibrate the acoustic impedance differences of mudstone and sandstone lithologies, suggesting that amplitude reflection is reliable and amplitude-dependent seismic attributes can be employed. The Root Mean Square (RMS) attribute confirmed the presence of thick-bedded braided channels. The results of cores and logging also confirmed the presence of braided channels and channel-bars. The test results of wells J34 and J72 shows that the reservoir quality within member-1 of LSF is favorable for gas production within the Hangjinqi area.