geological data
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The Nansen Legacy Q3 cruise, 5-27 August 2019, initiated the seasonal investigations of the Nansen Legacy transect. The transect represent an environmental gradient going through the northern Barents Sea, and included 7 process stations (P1-P7) lasting 6-53 hrs. CTD stations were taken to increase the hydrographic resolution on the transect. The program included measurements and sampling from the atmosphere, sea ice, ocean and sea floor. Data collected ranged from physical observations, chemical, biological and geological data collection, and the aim was to link observations and measurements to improve our understanding of the systems involving both climate, human impacts and the ecosystems. Deployment of moorings and gliders extended the observational capacity in time and space, outside the cruise period.

St. Ivan and St. Peter islands are located in the Black Sea at about 1200 m N-NW of the old town of Sozopol. There are many archeological structures on the St. Ivan island, in the same time the data on the archeological heritage of the St. Peter island are very scarce. In this research we present information about the archeological and geological features of both islands, with the focus of St. Peter, and probable reasons why the islands are separated from each other from a geological point of view.

Statistical analysis of a borehole database, linear discharges, and water strikes processing enabled an understanding of the structure, geometry and hydrodynamic properties of the metamorphic hard rock aquifers from the Montagnes District, Western Côte d’Ivoire. The database comprises 1654 boreholes among which 445 only were usable for this research work after its pre-processing. Analysis shows that the structure of the aquifer is similar to that observed in several other areas in the world: it developed due to weathering processes, comprises the capacitive saprolite, 10–20 m thick on average, and an underlying transmissive fractured layer, overlying the unweathered impermeable hard rock. The fractured layer is 80 m thick, the first 40 to 45 metres being its most productive zone, with a 11.3 m3/h median productivity. This research shows that metamorphic aquifers exhibit similar aquifer properties (thickness, hydrodynamic parameters) as plutonic ones and that there is interest in using such databases for research and other purposes. However, a rigorous pre-treatment of the data is mandatory, and geological data from published maps must be used instead of the geological data from the database. A previous methodology aiming at processing the boreholes’ linear discharges was improved. It notably appears that the slope method must be preferred to the percentile method.

Abstract. Increased availability and use of 3D-rendered geological models have provided society with predictive capabilities, supporting natural resource assessments, hazard awareness, and infrastructure development. The Geological Survey of Canada, along with other such institutions, has been trying to standardize and operationalize this modelling practice. Knowing what is in the subsurface, however, is not an easy exercise, especially when it is difficult or impossible to sample at greater depths. Existing approaches for creating 3D geological models involve developing surface components that represent spatial geological features, horizons, faults, and folds, and then assembling them into a framework model as context for downstream property modelling applications (e.g. geophysical inversions, thermo-mechanical simulations, and fracture density models). The current challenge is to develop geologically reasonable starting framework models from regions with sparser data when we have more complicated geology. This study explores the problem of geological data sparsity and presents a new approach that may be useful to open up the logjam in modelling the more challenging terrains using an agent-based approach. Semi-autonomous software entities called spatial agents can be programmed to perform spatial and property interrogation functions, estimations and construction operations for simple graphical objects, that may be usable in building 3D geological surfaces. These surfaces form the building blocks from which full geological and topological models are built and may be useful in sparse-data environments, where ancillary or a priori information is available. Critical in developing natural domain models is the use of gradient information. Increasing the density of spatial gradient information (fabric dips, fold plunges, and local or regional trends) from geologic feature orientations (planar and linear) is the key to more accurate geologic modelling and is core to the functions of spatial agents presented herein. This study, for the first time, examines the potential use of spatial agents to increase gradient constraints in the context of the Loop project (https://loop3d.github.io/, last access: 1 October 2021​​​​​​​) in which new complementary methods are being developed for modelling complex geology for regional applications. The spatial agent codes presented may act to densify and supplement gradient as well as on-contact control points used in LoopStructural (https://www.github.com/Loop3d/LoopStructural, last access: 1 October 2021) and Map2Loop (https://doi.org/10.5281/zenodo.4288476, de Rose et al., 2020). Spatial agents are used to represent common geological data constraints, such as interface locations and gradient geometry, and simple but topologically consistent triangulated meshes. Spatial agents can potentially be used to develop surfaces that conform to reasonable geological patterns of interest, provided that they are embedded with behaviours that are reflective of the knowledge of their geological environment. Initially, this would involve detecting simple geological constraints: locations, trajectories, and trends of geological interfaces. Local and global eigenvectors enable spatial continuity estimates, which can reflect geological trends, with rotational bias, using a quaternion implementation. Spatial interpolation of structural geology orientation data with spatial agents employs a range of simple nearest-neighbour to inverse-distance-weighted (IDW) and quaternion-based spherical linear rotation interpolation (SLERP) schemes. This simulation environment implemented in NetLogo 3D is potentially useful for complex-geology–sparse-data environments where extension, projection, and propagation functions are needed to create more realistic geological forms.

Research has been conducted using the gravity method in the Wai Selabung area, South Ogan Kemiring Ulu Regency, South Sumatra Province, correlated with geological data, magnetotellurics, and geochemical data. This research aims to get structural patterns, subsurface models and identify the heat source and reservoir areas of the Wai Selabung geothermal system. This study uses the gravity method to model the subsurface, which is correlated with magnetotelluric and geochemical data to identify reservoir prospect areas. The results obtained from this research include residual anomalies in the research area showing the presence of a northwest-southeast trending fault structure by the main fault structure of this area trending northwest-southeast and slightly southwest-northeast. Analysis of the Second Vertical Derivative value of zero indicates the boundaries of the geothermal reservoir in the middle of the research area.  The results of the 3D inversion modeling of the research area show that low density (2 to 2.15 g/cm3) indicates the location of the reservoir, medium-density values (2.2 to 2.4 g/cm3) are tertiary sandstone sedimentary. The high-density distribution value (2.5 to 2.9 g/cm3) indicates a potential heat source. And based on the analysis of the gravity method correlated with geological data, magnetotelluric, and geochemical data, the prospect area for the Wai Selabung geothermal reservoir, is around Teluk Agung, Perekan, and Talang Tebat.

Gas-emission craters discovered in northern West Siberia may arise under a specific combination of shallow and deep-seated permafrost conditions. A formation model for such craters is suggested based on cryological and geological data from the Yamal Peninsula, where shallow permafrost encloses thick ground ice and lenses of intra- and subpermafrost saline cold water (cryopegs). Additionally, the permafrost in the area is highly saturated with gas and stores large accumulations of hydrocarbons that release gas-water fluids rising to the surface through faulted and fractured crusts. Gas emission craters in the Arctic can form in the presence of gas-filled cavities in ground ice caused by climate warming, rich sources of gas that can migrate and accumulate under pressure in the cavities, intrapermafrost gas-water fluids that circulate more rapidly in degrading permafrost, or weak permafrost caps over gas pools.

Abstract Capacitance resistance models (CRM) constitute reduced physics-based models that provide quantitative first order estimate of inter-well connectivity using production and injection data (without geology). However, application of these models to mature fields with large number of wells along with historical data and varying operating conditions is challenging and computationally expensive. In this study we present a novel hybrid approach that combines CRM with geological data for application to large reservoirs. CRM models become more challenging, when applied in larger domains, because the number of unknowns they assume for every injector and producer pair are inherently connected. To overcome this complication, we obtain radius of investigation (ROI) for every injector using Fast Marching Model (FMM) that characterizes the field based on the geological data. Specifically, FMM is used to determine unrelated producer-injector pairs and ROI for each injector that reduce the number of unknowns and hence computational complexity. This hybrid model approach is validated by comparing results with a standalone CRM model for both synthetic and field data. We validate the proposed method results using synthetic data for a producing field with 5 producers and 4 injectors that is generated by numerical simulation. The FMM accurately identifies unrelated injection-production pairs to reduce the number of unknowns in CRM model by 35% (20 to 13). After conceptual validation, we apply this hybrid approach to a mature field with 29 injectors and 46 producers where the number of unknowns are reduced by 57% after the non-related pairs are determined with FMM. This results in significant speedup of computations as compared to standalone CRM approach. In totality, we have developed and validated the proposed hybrid model of geology and CRM using synthetic and field data. On applying our learnings successfully, we propose a hybrid model that combines two reduced-physics models (CRM and FMM) to decrease computational speed and reduce uncertainty in the field. With increasing focus on digitization, these workflows can help organizations reallocate water injection without CAPEX to deliver return on investment for digitization projects.