Petrophysical core-based zonation of OW oilfield in the Bredasdorp Basin South Africa

This study aims to generate rock units based on core permeability and porosity of OW oilfield in the Bredasdorp Basin offshore South Africa. In this study, we identified and classified lithofacies based on sedimentology reports in conjunction with well logs. Lucia's petrophysical classification method is used to classify rocks into three classes. Results revealed three lithofacies as A (sandstone, coarse to medium-grained), B (fine to medium-grained sandstone), and C (carbonaceous claystone, finely laminated with siltstone). Lithofacies A is the best reservoir quality and corresponds to class 1, while lithofacies B and C correspond to class 2 and 3, which are good and poor reservoir quality rock, respectively. An integrated reservoir zonation for the rocks is based on four different zonation methods (Flow Zone indicator (FZI), Winland r35, Hydraulic conductivity (HC), and Stratigraphy modified Lorenz plot (SMLP)). Four flow zones Reservoir rock types (RRTs) were identified as RRT1, RRT3, RRT4, and RRT5, respectively. The RRT5 is the best reservoir quality composed of a megaporous rock unit, with an average FZI value between 5 and 10 µm, and HC from 40 to 120 mD/v3, ranked as very good. The most prolific flow units (RRT5 and RRT4 zones) form more than 75% of each well's flow capacities are supplied by two flow units (FU1 and FU3). The RRT1 is the most reduced rock quality composed of impervious and nanoporous rock. Quartz is the dominant framework grain, and siderite is the dominant cement that affects flow zones. This study has demonstrated a robust approach to delineate flow units in the OW oilfield. We have developed a useful regional petrophysical reservoir rock flow zonation model for clastic reservoir sediments. This study has produced, for the first time, insights into the petrophysical properties of the OW oilfield from the Bredasdorp Basin South Africa, based on integration of core and mineralogy data. A novel sandstone reservoir zonation classification criteria developed from this study can be applied to other datasets of sandstone reservoirs with confidence.

Surface damage from perpendicular and oblique bullet impacts in stone

Controlled experiments were conducted to investigate the surface damage caused by perpendicular and oblique impacts of bullets into sandstone and limestone targets. Individual bullets fired in conditions simulating modern rifles at typical combat distances excavated craters with diameters from 22 to 74 mm and depths from 4 to 24 mm. Limestone target craters were up to twice as large and deep as those in sandstone. These craters have a complex shape consisting of a central excavation surrounded by a shallow dish, compared to the simple bowl shape of most sandstone impacts. Radial fractures extending to the edge of the target block were common in limestone targets. Impacts at an angle of 45° to the surface in both rock types result in asymmetric craters. Two common types of ammunition were compared: the steel-tipped NATO projectile generally produced larger and deeper craters than the projectile that is commonly fired from AK-47 rifles, despite having approximately half the mass of the latter. These results characterise the sort of damage that can be expected at many sites of cultural significance involved in contemporary conflict zones, and have important implications for their conservation.

Digital Rock Typing DRT Algorithm Formulation with Optimal Supervised Semantic Segmentation

<p><a></a>Each grid block in a 3D geological model requires a rock type that represents all physical and chemical properties of that block. The properties that classify rock types are lithology, permeability, and capillary pressure. Scientists and engineers determined these properties using conventional laboratory measurements, which embedded destructive methods to the sample or altered some of its properties (i.e., wettability, permeability, and porosity) because the measurements process includes sample crushing, fluid flow, or fluid saturation. Lately, Digital Rock Physics (DRT) has emerged to quantify these properties from micro-Computerized Tomography (uCT) and Magnetic Resonance Imaging (MRI) images. However, the literature did not attempt rock typing in a wholly digital context. We propose performing Digital Rock Typing (DRT) by: (1) integrating the latest DRP advances in a novel process that honors digital rock properties determination, while; (2) digitalizing the latest rock typing approaches in carbonate, and (3) introducing a novel carbonate rock typing process that utilizes computer vision capabilities to provide more insight about the heterogeneous carbonate rock texture.<br></p>

Digital Rock Typing DRT Algorithm Formulation with Optimal Supervised Semantic Segmentation

<p><a></a>Each grid block in a 3D geological model requires a rock type that represents all physical and chemical properties of that block. The properties that classify rock types are lithology, permeability, and capillary pressure. Scientists and engineers determined these properties using conventional laboratory measurements, which embedded destructive methods to the sample or altered some of its properties (i.e., wettability, permeability, and porosity) because the measurements process includes sample crushing, fluid flow, or fluid saturation. Lately, Digital Rock Physics (DRT) has emerged to quantify these properties from micro-Computerized Tomography (uCT) and Magnetic Resonance Imaging (MRI) images. However, the literature did not attempt rock typing in a wholly digital context. We propose performing Digital Rock Typing (DRT) by: (1) integrating the latest DRP advances in a novel process that honors digital rock properties determination, while; (2) digitalizing the latest rock typing approaches in carbonate, and (3) introducing a novel carbonate rock typing process that utilizes computer vision capabilities to provide more insight about the heterogeneous carbonate rock texture.<br></p>

The smallest space miners: principles of space biomining

As we aim to expand human presence in space, we need to find viable approaches to achieve independence from terrestrial resources. Space biomining of the Moon, Mars and asteroids has been indicated as one of the promising approaches to achieve in-situ resource utilization by the main space agencies. Structural and expensive metals, essential mineral nutrients, water, oxygen and volatiles could be potentially extracted from extraterrestrial regolith and rocks using microbial-based biotechnologies. The use of bioleaching microorganisms could also be applied to space bioremediation, recycling of waste and to reinforce regenerative life support systems. However, the science around space biomining is still young. Relevant differences between terrestrial and extraterrestrial conditions exist, including the rock types and ores available for mining, and a direct application of established terrestrial biomining techniques may not be a possibility. It is, therefore, necessary to invest in terrestrial and space-based research of specific methods for space applications to learn the effects of space conditions on biomining and bioremediation, expand our knowledge on organotrophic and community-based bioleaching mechanisms, as well as on anaerobic biomining, and investigate the use of synthetic biology to overcome limitations posed by the space environments.

Characteristics and influencing factors of Cretaceous reservoir in eastern depression of North Yellow Sea basin

Cretaceous is the key exploration target layer in the eastern depression of North Yellow Sea basin, which has a good prospect for oil and gas exploration. Its huge oil and gas resource potential has attracted great attention from petroleum geologists. In this study, the main rock types, reservoir space types, petrophysical characteristics and main controlling factors of Cretaceous reservoir are studied through core observation, thin section identification, petrophysical analysis and scanning electron microscope observation. The results indicate that the main rock types of Cretaceous reservoir in the eastern depression of North Yellow Sea basin are lithic arkose, feldspar lithic sandstone, some feldspar sandstone and a small amount of lithic sandstone. The average porosity is 6.9%, and the average permeability is 0.46 × 10−3 μm, so Cretaceous reservoir in the study area has poor petrophysical characteristics and belongs to low porosity and low permeability reservoir. Cretaceous reservoirs in the study area mainly develop in secondary pores, which are dominated by dissolution pores (including intragranular pores, intercrystalline pores and cleavage pores), followed by fractures. The main factors affecting petrophysical characteristics of Cretaceous reservoir in the study area are provenance properties, sedimentation, diagenesis (including compaction, cementation and dissolution) and tectonism. The provenance properties and sedimentation are the prerequisite conditions affecting petrophysical characteristics. Petrophysical characteristics of feldspar sandstone of Cretaceous reservoir in the study area and lithic arkose are better than that of feldspar lithic sandstone. Both compaction and cementation reduce the porosity and permeability of Cretaceous reservoir in the study area and make petrophysical characteristics become poor, whereas the dissolution and tectonism play an important role in improving petrophysical characteristics of Cretaceous reservoir.

Geochemistry and tectonic setting for the deposition of IOG siliciclastics at the western margin of Bonai Granite, Singhbhum-Orissa Craton, India

Bagiyabahal and Birtola areas are located in the south-western extension of the Noamundi-Koira Iron Ore Group (IOG) basin. Rock types exposed in the area comprises of siliciclastics and volcanics which occurs unconformably over the basement tonalite-trondhjemite granite-gneiss (Bonai Granite Phase-I). The cover rocks show sheared contact with the porphyritic Bonai Granite Phase-II. The IOG basin margin is suggested to be a part of a ‘volcanic passive margin’ as indicated by the geochemical behaviour of the siliciclastics as well as massive emplacements of mafic intrusives (doleritic sill, dyke and gabbro) and extrusives (basaltic lava flow) along faulted continental blocks. The siliciclastics comprise of U and Au bearing quartz-pebble conglomerate (QPC) and quartzite succession. It was deposited along the western margin of the Bonai granite (phase I) in anoxic conditions as indicated by their low Th/U ratios and presence of detrital uraninite grains. Repeated cycles of sedimentation and volcanism led to the formation of alternate layers of siliciclastics and basic bodies in the area. Major, trace and rare earth elements (REE) geochemical data suggests a semi-humid to humid palaeo-climatic environment of during the deposition in the passive continental margin setting characterized by fault-controlled sedimentation over a rift related faulted continental crust and shelf. Geochemical data suggests chemically weathered provenance dominated by clay minerals. Higher content of U, Th, Au, Cr, REE, platinum group of elements (PGE) and other geochemical ratios suggest a mixed provenance for the deposition of the siliciclastics comprising a predominantly acidic/granitic source possibly from the Bonai Granitic Complex (BGC) along with granite derived reworked quartzose sediments, minor basic and ultrabasic sources of Older Metamorphic Group (OMG). This paper attempts to characterize the geochemical behaviour, tectonic setting and provenance of the siliciclastics of Birtola and Bagiyabahal areas by analyzing drill core and surface samples.

The Effect of Heat Shocks and Freezing–Thawing Cycles on the Mechanical Properties of Natural Building Stones

The damage to rock masses due to the action of freezing is one of the most important factors in the development of landscapes, the performance of civil structures, and the efficiency of mining operations. In this research paper, the effect has been studied on the physical and mechanical performance of seven different natural building rock samples. The testing program included an experimental study on both dry and saturated intact rock samples and therefore, the effect of saturation on the extent of damage on the tested samples has been discussed as well. Based on the obtained results, freezing–thawing cycles increase the porosity of rock samples and decrease the values of P-wave velocity, uniaxial compressive strength, elastic modulus, and Brazilian tensile strength. Moreover, the behavior of different rock types differs to some extent when exposed to weathering cycles under dry and saturated conditions. A multivariate linear regression analysis was used to predict the changes in the physical and mechanical properties of different rock types. It was been shown that with some cautions, the obtained correlations can be generalized for practical cases and can be used to predict the change of rock physical and mechanical properties during the lifetime of rock engineering projects. Such predictions have a high potential of applicability in quite different types of natural stone applications in cold climates. From the stability of structures created in rock materials to the durability of structures created by different natural stones.

Carbonate reservoir rock typing algorithm based on integrated approach (IRT)

The goal of carbonate rock typing is a realistic distribution of well data in a 3D model and the distribution of the corresponding rock types, on which the volume of hydrocarbon reserves and the dynamic characteristics of the flow will depend. Common rock typing approaches for carbonate rocks are based on texture, pore classification, electrofacies, or flow unit localization (FZI) and are often misleading because they based on sedimentation processes or mathematical justification. As a result, the identified rock types may poorly reflect the real distribution of reservoir rock characteristics. Materials and methods. The approach described in the work allows to eliminate such effects by identifying integrated rock types that control the static properties and dynamic behavior of the reservoir, while optimally linking with geological characteristics (diagenetic transformations, sedimentation features, as well as their union effect) and petrophysical characteristics (reservoir properties, relationship between the porosity and permeability, water saturation, radius of pore channels and others). The integrated algorithm consists of 8 steps, allowing the output to obtain rock-types in the maximum possible way connecting together all the characteristics of the rock, available initial information. The first test in the Middle East field confirmed the applicability of this technique. Results. The result of the work was the creation of a software product (certificate of state registration of the computer program “Lucia”, registration number 2021612075 dated 02/11/2021), which allows automating the process of identifying rock types in order to quickly select the most optimal method, as well as the possibility of their integration. As part of the product, machine learning technologies were introduced to predict rock types based on well logs in intervals not covered by coring studies, as well as in wells in which there is no coring.