Field Scale Research Articles

Multiscale fracture, physical and mechanical properties of stromboli volcano (Italy) edifice

The physical, mechanical and fracture properties at Stromboli volcano have been integrated at multiple scales to understand whether the interplay between a presumed NE/SW rift zone and the Sciara del Fuoco (SDF) depression has resulted in a zone of weakness able to promote fracturing prone to flank instability. Multiscale fracture quantification by imaging via FracPaQ toolbox both fractures and sample scale fractures has been integrated with rock physics and rock mechanics experiments on cm-scale samples belonging to the Paleostromboli, Vancori, Neostromboli, Pizzo and Present Deposit volcanic cycles that have been taken from within and outside the rift zone. The structural changes to the edifice have been quantitively assessed by mapping at different scale fracture properties such density and orientation within and outside the rift zone allowing to identify the potential damaged zones that could reduce the edifice strength.Results indicate that basalt textures, microfracture density, porosity, chemical zoning and preferential alignments, despite lithologically dependent, can be related to the NE/SW zone of weakness at the regional scale and to collapsed volumes that have been subject to continuous intrusive activity. Numerical inversion models have been performed to cross correlate fracture density in the basalts at multiple scales.A link between microfracture density and seismic velocities has been also established via numerical modelling, allowing to interpret in terms of degree of fracturing the results of seismic tomographies at the field scale, providing a novel method to image crack damage evolution within the inner structure of the volcano edifice.

An Integrated Petrographic, Geomatic and Geophysical Approach for the Characterization of the Carbonate Rocks of the Calcari di Cagliari Formation

Non-invasive techniques, such as close-range photogrammetry (CRP) and 3D ultrasonic tomography complemented with optical and scanning electron microscopy and mercury porosimetry, were applied to characterize the carbonate rock samples of the Calcari di Cagliari formation. The integrated approach started with the computation of high-resolution 3D models of the carbonate samples using the CRP technique to produce 3D high-resolution models texturized both with natural colors and intensity. Starting from the 3D models from previous techniques, a 3D ultrasonic tomography on each rock sample was accurately planned and carried out in order to detect the elastic properties of such rocks and relate them to textural heterogeneity or internal defects. The results indicate that the relationship between longitudinal velocity and rock properties is complex even in the same carbonate formation. Understanding the relationship between the geomatic and geophysical responses in the investigated rock properties, such as textural characteristics and especially structure and geometry of pores, type of pores, tortuosity and cementing material, is important for many practical applications and especially in the diagnostic process of the conservation state of monumental structures. The integration of the above non-invasive techniques complemented by petrographical–petrophysical data proved to be a powerful method to associate each lithotype with a different susceptibility to degradation. The results presented in this paper demonstrate that the proposed integrated use of complementary methodologies would guarantee the reproducibility of the measurements both at the laboratory and field scale for the monitoring in time of the rock condition while giving a useful contribution in making decisions on an appropriate remedial strategy.

Estimating major merger rates and spin parameters ab initio via the clustering of critical events

Abstract We build a model to predict from first principles the properties of major mergers. We predict these from the coalescence of peaks and saddle points in the vicinity of a given larger peak, as one increases the smoothing scale in the initial linear density field as a proxy for cosmic time. To refine our results, we also ensure, using a suite of ∼400 power-law Gaussian random fields smoothed at ∼30 different scales, that the relevant peaks and saddles are topologically connected: they should belong to a persistent pair before coalescence. Our model allows us to (a) compute the probability distribution function of the satellite-merger separation in Lagrangian space: they peak at three times the smoothing scale; (b) predict the distribution of the number of mergers as a function of peak rarity: haloes typically undergo two major mergers (>1:10) per decade of mass growth; (c) recover that the typical spin brought by mergers: it is of the order of a few tens of percent.

Estimating soil salinity in mulched cotton fields using UAV-based hyperspectral remote sensing and a Seagull Optimization Algorithm-Enhanced Random Forest Model

Xinjiang is a crucial production base for mulched cotton fields but faces increasingly severe challenges of soil salinization. Under the current drive towards precision agriculture, high precision monitoring of agricultural conditions at the field scale has become critical. Traditional remote sensing technologies are limited by insufficient spatial and spectral resolution, making field monitoring under mulched conditions exceptionally challenging. This study introduces a novel approach combining drone-based hyperspectral remote sensing with the Seagull Optimization Algorithm-Enhanced Random Forest Model (SOA-RF). After employing the preprocessing techniques of standard normal variable (SNV) and fractional order derivative (FOD), we employed the model to assess the level of field-scale salinization under optimization of feature selection using separate dimensionality reduction algorithms (sequential projection algorithm (SPA), optimal band combination analysis (OBCA)) and a combined approach (SPA-OBCA). The following main results were found: (1) SNV and FOD enhanced the spectral characteristics of cotton canopies, with the FOD technique performing better in detecting subtle signal changes in the positive and negative peaks of the spectrum. (2) SPA and OBCA were effective in screening the soil salt-sensitive bands in cotton canopies but the combined SPA-OBCA method provided a better selective preference for hyperspectral bands, with an optimal correlation of 0.926. (3) The model combined the advantages of SOA with the power of Random Forest to optimize the parameters and improve the estimation accuracy (R2 = 0.925, RPD = 4.128). We used unmanned aerial vehicle hyperspectral imagery to create a 5-cm resolution map of soil salinity distribution in cotton fields that allowed detection of differences in soil salinity between mulches, thus providing a scientific basis for soil salinity management and the development of precision agriculture.

Graphite Content Identification with Laboratory and Field Spectral Induced Polarization Measurements

Graphite, a critical raw material, prompts interest in assessing former quarries for volumetric content, driving the need for accurate prospection techniques. We explore the efficacy of spectral induced polarization (SIP) imaging at field scale for this purpose. Field measurements in a quarry with unknown graphite content underscore the need for assessment before drilling due to abrupt topography. Due to the lack of ground truth required to calibrate existing petrophysical models, we propose using SIP laboratory measurements to achieve the quantitative interpretation of the imaging results. We conducted experiments at two scales: rock plugs for material response and ground rocks of varying sizes for textural analysis. The rock plugs allow us to investigate the response of the material, while the ground samples permit us to understand changes in the SIP response for varying textural properties. Our lab work establishes power-law relationships between polarization (expressed in terms of normalized chargeability) and graphite content, as well as relaxation time and grain size. Salinity dependence is noted between chargeability, normalized chargeability, and relaxation time. Utilizing these findings, we provide a quantitative interpretation of field SIP imaging results.

Fault and fracture network characterization using soft computing techniques: application to geologically complex and deeply-buried geothermal reservoirs

Geothermal energy is a sustainable energy source that meets the needs of the climate crisis and global warming caused by fossil fuel burning. Geothermal resources are found in complex geological settings, with faults and interconnected networks of fractures acting as pathways for fluid circulation. Identifying faults and fractures is an essential component of exploiting geothermal resources. However, accurately predicting fractures without high-resolution geophysical logs (e.g., image logs) and well-core samples is challenging. Soft computing techniques, such as machine learning, make it possible to map fracture networks at a finer resolution. This study employed four supervised machine learning techniques (multilayer perceptron (MLP), random forests (RF), extreme gradient boosting (XGBoost), and support vector regression (SVR)) to identify fractures in geothermal carbonate reservoirs in the sub-basins of East China. The models were trained and tested on a diverse well-logging dataset collected at the field scale. A comparison of the predicted results revealed that XGBoost with optimized hyperparameters and data division achieved the best performance than RF, MLP, and SVR with RMSE = 0.02 and R2 = 0.92. The Q-learning algorithm outperformed grid search, Bayesian, and ant colony optimizations. The blind well test demonstrates that it is possible to accurately identify fractures by applying machine learning algorithms to standard well logs. In addition, the comparative analysis indicates that XGBoost was able to handle the complex relationship between input parameters (e.g., DTP > RD > DEN > GR > CAL > RS > U > CNL) and fracture in geologically complex geothermal carbonate reservoirs. Furthermore, comparing the XGBoost model with previous studies proved superior in training and testing. This study suggests that XGBoost with Q-learning-based optimized hyperparameters and data division is a suitable algorithm for identifying fractures using well-log data to explore complex geothermal systems in carbonate rocks.Graphical abstract

Biodegradable film mulching increases soil microbial network complexity and decreases nitrogen-cycling gene abundance

Biodegradable plastic films have emerged as a substitute for conventional plastic films. Nevertheless, responses of plant-associated microbiomes to the application of biodegradable film mulching at field scale have received little attention. A field experiment was conducted to assess the influence of different film mulching treatments on various microbial attributes and nitrogen (N) cycling functional genes in bulk and rhizosphere soils. Biodegradable film mulching raised the bacterial Shannon index in bulk soils but not in rhizosphere soils. Biodegradable film mulching has led to an increase in the complexity and connectivity of microbial networks, as well as an enhancement in the positive association among microorganisms owing to raised soil nutrients and increased crop biomass. In biodegradable film-treated soils, both bacterial and fungal communities were primarily influenced by stochastic processes associated with dispersal limitation. Moreover, conventional plastic film mulching increased denitrification, anammox, N fixation, and dissimilatory nitrate-reduction (DNRA) gene abundance in bulk soils. In rhizosphere soils, biodegradable film mulching reduced nitrification, denitrification, anammox, N fixation, and DNRA gene abundance. Furthermore, keystone genera (e.g., Nitrosospira, Truepera, Adhaeribacter, Opitutus, and Fusarium) were affected by edaphic variables, contributing to decreased N-cycling gene abundance in biodegradable film-treated soils. Collectively, biodegradable film mulching transformed soil microbiome assembly and functional adaptation, and soil nutrient availability and plant biomass were the critical factors influencing the microbial community. These findings present a novel perspective on the diverse impacts of biodegradable and conventional film mulching on soil microbiome and N-cycling processes.

Predicting soil nutrients with PRISMA hyperspectral data at the field scale: the Handan (south of Hebei Province) test cases

ABSTRACT This research investigates the suitability of PRISMA and Sentinel-2 satellite imagery for retrieving topsoil properties such as Organic Matter (OM), Nitrogen (N), Phosphorus (P), Potassium (K), and pH in croplands using different Machine Learning (ML) algorithms and signal pre-treatments. Ninety-five soil samples were collected in Quzhou County, Northeast China. Satellite images captured soil reflectance data when bare soil was visible. For PRISMA data, a Linear Mixture Model (LMM) was used to separate soil and Photosynthetic Vegetation (PV) endmembers, excluding Non-Photosynthetic Vegetation (NPV) using Band Depth values at the 2100 nm absorption peak of cellulose. Sentinel-2 bare soil reflectance spectra were obtained using thresholds based on NDVI and NBR2 indices. Results showed PRISMA data provided slightly better accuracy in retrieving topsoil nutrients than Sentinel-2. While no optimal predictive algorithm was best, absorbance data proved more effective than reflectance. PRISMA results demonstrated potential for predicting soil nutrients in real scenarios.

Prediction of the Effects of Pulsating Hydraulic Fracturing on the Porous Structure and Permeability of Coal Based on NMR and AE Spectra.

Pulsating hydraulic fracturing has been an environmentally friendly method to improve the permeability of rock formations to stimulate gas production and reduce hazard risks. It has the advantage of fracturing the reservoir with lower cracking pressure and less water volume, as the mechanical strength of rock materials has been reduced by the hydraulic pulse pressure. Many researchers have found significant changes in hard rocks after cyclic loading. However, the existing work still cannot clearly explain the mechanism of the rock damage by pulsating hydraulic fracturing within a short-time experiment. To solve the issue, an investigation of the effects of pulsating hydraulic fracturing on CBM production has been carried out in lab and field applications. Results indicate that the long-term hydraulic pulse pressure can cause a linear decline in cracking pressure directly measured in the lab. It plays an essential role in the permeability enhancement by generating more flow channels for CBM production. The low-field NMR quantitatively evaluates the increase in porosity, which reveals significant incremental ratios of over 20% in the porosity of macropores, mesopores, and micropores of coal caused by fatigue damage. It is first proven that hydraulic pulse pressure has a significant influence on the porosity components of macropores, mesopores, and micropores. To validate the effectiveness of the technique on the field scale, a field application of pulsating hydraulic fracturing has been carried out in a coal mine. It shows that gas production has been largely enhanced with a long and stable production stage and higher gas flux after the applied pulsating load. The gas concentration and gas flux of the fractured boreholes are about 2 times that of the nonfractured boreholes. This work provides an investigation of the effects of pulsating hydraulic fracturing on CBM production, which gives a better understanding of the mechanism for the engineers in the field.

Field monitoring and modelling of sediment transport, hydraulics and hydroabrasion at Sediment Bypass Tunnels

Sediment Bypass Tunnels (SBTs) are proven to be an effective measure to reduce or even stop reservoir sedimentation by bypassing sediment laden flows around reservoir dams to the downstream river reach. They are mostly used in Switzerland, Japan, and Taiwan. However, hydraulic and sedimentological operating conditions and the resistance of the invert materials against hydroabrasive erosion affect their cost-effectiveness. Hydroabrasion is a pressing issue at SBTs, other hydraulic structures and steep bedrock rivers exposed to high sediment transport rates under supercritical flow conditions. The present study was therefore conducted to address this issue by aiming at improving knowledge on abrasion mechanics and calibrating a mechanistic saltation abrasion model enhanced by Demiral-Yüzügüllü (2021). To this end, the abrasion resistance of fourteen different invert materials installed at Solis, Pfaffensprung and Runcahez SBTs in Switzerland was quantified by annual 3D laser scanning and the hydraulic conditions and sediment transport rates were regularly monitored between 2017 and 2021. The analysis of invert scans and hydraulic conditions revealed that Prandtl’s first and second kinds of secondary currents occurring in the bends and straight sections of the SBTs, respectively, and the observed abrasion patterns were strongly interrelated. The tested potassium aluminate cement and steel fibre concretes, granite, cast basalt and steel plates had better abrasion resistance against impact of sediment-laden flows compared to other materials. Sediment mineralogical composition i.e., bulk hardness relative to the invert material properties significantly affected hydroabrasion. The enhanced abrasion prediction model was calibrated with the present data and a quasi-constant abrasion coefficient of kv = (4.8 ± 2.2) × 104 was obtained. The enhanced model is well-suited for both laboratory and field scales. The present findings will contribute to the sustainable utilization and operational safety of hydraulic structures, optimization of SBT and reservoir operations regarding bypassing efficiency and reservoir lifetime and modelling of bedrock river erosion.

Pepper mild mottle virus as an effective tool in microbial source tracking for deficient domestic on-site water treatment systems

Pollution from domestic on-site wastewater treatment systems (OWTS) is a significant contaminant pressure in many rural catchments. However, due to their design, and dispersed proliferation, it is difficult to assess their impact. Water testing methodologies employ bacterial culturing methods and chemical analysis which may lose resolution and/or specificity being confounded by diffuse agricultural sources within a rural environment. In this study, we successfully assessed the applicability of Pepper Mild Mottle Virus (PMMoV) as a human faecal source tracker for deficient on-site wastewater treatment systems. The transport of PMMoV was first studied in the effluent of a 30 cm deep soil column which was dosed for 510 days with primary influent from a conventional septic system. The removal of PMMoV through the 30 cm deep soil column was quantified with a 5-day seeding trial employing primary influent mixed with PMMoV sourced from Tabasco pepper product ®. The trial was then carried out at field scale with the seeding solution dosed into an operational percolation trench receiving septic tank effluent which had been instrumented for porewater sampling. Samples were taken at depths of 10 cm, 30 cm, and 50 cm across the length of the trench at distances of 1 m, 7.5 m, and 17.5 m from the inlet of the trench. PMMoV was detected on all days of the trial, with a peak concentration of 1 × 106 found at the rear of the trench on day 2 of the seeding trial. Finally, to assess the effectiveness of PPMoV as a microbial source tracking tool from a water receptor perspective, three rural catchments with high densities of OWTSs were sampled and analysed for hourly variations in biological parameters which included total coliforms, Escherichia coli, PMMoV, and chemical parameters total organic carbon, total nitrogen, and total carbon. PMMoV was detected in all river samples over a 24-hour period, thereby indicating its suitability as a tracer of human wastewater effluent in such environments with multiple diffuse sources.

Research on the unsteady flow field and aerodynamic noise characteristics in the circular space of ultra-high-speed elevators

Due to the non-streamlined blunt body shape of the elevator car, intense aerodynamic loads and noise are generated in the annular space when the elevator operates at high speed in a narrow hoistway. This article uses large-eddy simulation and Curle acoustic theory to establish a numerical model of the wellbore flow field under different guiding shapes of the elevator car. First, the mechanism of action between the flow guide shape, vortex characteristics, and aerodynamic load was studied, and the influence of operating speed on aerodynamic load under different flow guide shapes was analyzed. Second, the distribution and spectral characteristics of noise in the annular space under different flow guide shapes were studied from the near field and far field scales. Finally, it can be concluded that increasing the guide surface can significantly reduce the pressure difference between the upper and lower parts of the car, weakening the separation of the tail airflow. The number of guide surfaces, installation position, and vertex offset significantly impact drag and lateral force, with the optimal reduction of 34.65% and 57.6%, respectively. The maximum sound source intensity of near-field noise is mainly concentrated at the arc transition in the upper part of the annular space, and the frequency is mainly concentrated in the range of 500–1000 Hz. The sound pressure level is linearly related to the logarithm of the longitudinal distance, and the noise attenuation speed becomes faster with the increase in the number of guiding surfaces.

Black holes in degenerate Einstein Gauss-Bonnet gravity: can QNMs distinguish them from GR?

For the first time, we study the quasi-normal modes(QNMs) of massless scale fields propagating in spacetimes with zero metric determinant. In this context, we work with asymptotically flat solutions to degenerate Einstein-Gauss-Bonnet (EGB) theory introduced in [JCAP 02 (2022) 020]. This solution has two distinct branches akin to Einstein Gauss-Bonnet(EBG) gravity. However, unlike the EBG solutions, both the branches of dEGB are well-defined asymptotically. The negative branch solutions from both theories are equivalent under the identification of certain parameters. We provide constraints on the Gauss-Bonnet coupling parameters, which result in black hole spacetimes, and study the behaviour of a propagating scalar field through the computation of QNMs. Finally, we compare the time domain evolution of the scalar field in the background of these black holes with their GR counterparts.

Image Super-resolution Networks based on Structure Reparameterized Convolution

The traditional image super resolution method based on convolutional neural network generally brings two problems: First, the model has only a single scale of receptive field, which cannot use the image information in a smaller range; Second, the size of the feature map will become smaller and smaller in the process of continuous convolution, and it is necessary to continuously carry out edge zeroing operation to maintain the original size, which leads to the loss of part of the edge information. To solve the above two problems, we propose a network structure based on structure re-parameterized convolution, which sets a small convolution kernel in parallel beside a large convolution kernel in the same layer, trains the two cores simultaneously, and finally merges the two cores. The experimental results show that in this way, we make the large convolution kernel could capture smaller information, which not only improves the high-frequency details of the reconstructed image but also avoids frequent edge filling to reduce the information density, and effectively speeds up the reasoning speed after the model is re-parameterized. Compared with the advanced methods, our method achieves good results.

Tackling capacitive coupling in broad-band spectral electrical impedance tomography (sEIT) measurements by selecting electrode configurations

SUMMARY Electromagnetic (EM) coupling effects including both inductive and capacitive coupling have long been an essential problem in broad-band spectral electrical impedance tomography (sEIT) measurements at the field scale. Efforts have been made to remove EM coupling numerically or to suppress the effects by modified data acquisition strategies. For near-surface applications with relatively small survey layouts, inductive coupling can be well removed in the mHz to kHz frequency range. With the use of shielded coaxial cables and so-called active electrodes where the amplifiers are mounted at the electrodes, capacitive coupling in sEIT measurements can also be reduced. However, it remains challenging to cope with capacitive coupling between the cable shield and the ground, especially in resistive field conditions. The aim of this study is to deal with this type of capacitive coupling effect by identifying and filtering out sEIT measurements that are strongly affected by capacitive coupling. Based on a correction method for capacitive coupling proposed in a previous study, an approach to estimate measurement errors due to capacitive coupling is presented first. In the second step, a workflow was proposed to calculate the capacitive coupling strength (CCS) for each electrode configuration, which is defined as the ratio of the imaginary part of the impedance induced by capacitive coupling and the imaginary part of the impedance due to the subsurface electrical conductivity. In the final step, measurements with low CCS were selected for inversion and the results were compared with inversion results obtained using the previously developed correction approach. It was found that the filtering method based on CCS is more capable in tackling capacitive coupling compared to using model-based corrections. Spectrally consistent sEIT results up to kHz were obtained using the newly developed filtering method, which were not achieved in previous work using model-based correction.

Experimental seismic crosshole setup to investigate the application of rock-physical models at the field scale

Seismic crosshole techniques are powerful tools to characterize the properties of near-surface aquifers. Knowledge of rock-physical relations at the field scale is essential for interpreting geophysical measurements. However, it remains difficult to extend the results of existing laboratory studies to the field scale due to the usage of different frequency ranges. To address this, we develop an experimental layout that successfully determines the dependency of gas saturation on seismic properties. Integrating geophysical measurements into a hydrogeologic research question allows us to prove the applicability of theoretical rock-physical concepts at the field scale, filling a gap in the discipline of hydrogeophysics. We use crosshole seismics to perform a time-lapse study on a gas injection experiment at the TestUM test site. With a controlled two-day gaseous [Formula: see text] injection at a depth of 17.5 m, we monitor the alteration of water saturation in the sediments over a period of 12 months, encompassing an observational depth of 8–13 m. The investigation contains an initial P-wave simulation followed by a data-based P-wave velocity analysis. Subsequently, we discuss different approaches to quantifying gas content changes by comparing Gassmann’s equation and the time-average relation. With the idea of patchy saturation, we discover that analyzing P-wave velocities in the subsurface is a suitable method for our experiment, resulting in a measurement accuracy of 0.2 vol%. We determine that our seismic crosshole setup is able to describe the relation of the rock’s elastic parameter on modified fluid properties at the field scale. With this method, we are able to quantify the relative water content changes in the subsurface.

Within‐field soil moisture variability and time‐invariant spatial structures of agricultural fields in the US Midwest

AbstractUnderstanding soil moisture variability and estimating high‐resolution soil moisture at subfield to field scales is critical for agricultural research and applications. However, systematic investigation of subfield scale soil moisture variability over cropland is still lacking from both measurement and satellite remote sensing. In this study, we aim to investigate (1) the characteristics of within‐field soil moisture distribution over typical cropland in the US Midwest and (2) the capabilities of satellite remote sensing in capturing the spatiotemporal variabilities of soil moisture at subfield scale. Specifically, we conducted soil moisture field experiments in three typical commercial agricultural fields (∼85 acres per field) in central Illinois, representing typical commercial farmlands in the US Midwest, and compared the soil moisture measurements with satellite remote sensing data from optical and active microwave sensors. In each field, dense soil moisture samples (spaced at 50–60 m) were obtained for two dry down events in May and July 2021, and multiple long‐term soil moisture stations were installed. We found prominent time‐invariant spatial structures of soil moisture at within‐field scales both during the dry down period and over longer time scales, and the stability is minimally affected by plant water use during the growing season. Comparing the field campaign measurements with satellite remote sensing data, we found that surface reflectance of shortwave infrared bands, such as SWIR1 (1610 nm) from Sentinel‐2, can capture relative surface soil moisture patterns at within‐field scales, but their relationships with soil moisture are field specific. These findings and the improved understanding of within‐field soil moisture dynamics could potentially help future research on high‐resolution soil moisture estimation with multi‐source remote sensing data.

Application of 1D model for overland flow simulations on 2D complex domains

High computational demand limits the applications of two-dimensional (2D) shallow water equation models for high resolution overland flow simulations, while one-dimensional (1D) models can achieve higher computing efficiency. This study applied a 1D hydrodynamic model to surrogate 2D models for overland flow simulations on complex 2D domains. With one dimension reduced, the surrogate model simulation would have acceptable accuracy with much higher computing efficiency. The surrogating is fulfilled through mimicking 2D models in mesh generations, so that the 1D channel network is generated in such a way that it geometrically covers the whole domain without overlapping and intersection, and hydrologically follows the steepest slopes. Several benchmark cases on 2D domains in both laboratory and field scales with complex geometry, where no 1D models have been ever applied, are used to compare the 1D and 2D model simulations. The comparisons demonstrate that the 1D model does have potentials to efficiently simulate overland flow on 2D complex domains with accuracy comparable to 2D models.

State of the Art on Fe Precipitation in Porous Media: Hydrogeochemical Processes and Evolving Parameters

The mixing of terrestrial groundwater and seawater creates dynamic reaction zones in intertidal areas, where land-derived Fe(II) is oxidized to Fe(III) and then precipitates as Fe hydroxides at the groundwater–seawater interface. These hydrogeochemical processes contribute to the formation of iron bands at the saltwater wedge (SW) and beneath the upper saline plume (USP). This study provides a comprehensive review of physical and geochemical processes at field scale in coastal areas, explores the impact of mineral precipitation on pore structure at pore scale, and synthesizes reactive transport modeling (RTM) approaches for illustrating continuum-scale soil physio-chemical parameters during the evolution of porous media. Upon this review, knowledge gaps and research needs are identified. Additionally, challenges and opportunities are presented. Therefore, we reach the conclusion that the incorporation of observational data into a comprehensive physico-mathematical model becomes imperative for capturing the pore-scale processes in porous media and their influence on groundwater flow and solute transport at large scales. Additionally, a synergistic approach, integrating pore-scale modeling and non-invasive imaging, is equally essential for providing detailed insights into intricate fluid–pore–solid interactions for future studies, as well as facilitating the development of regional engineering-scale models and physio-chemical coupled models with diverse applications in marine science and engineering.

A lookback study of well performance using borehole image data

The main objective of this work is to understand the impact of fracture, stress, drilling direction, and other reservoir properties on the production performance of a horizontal well (HW) in the Karachaganak Field. Taking advantage of the 70 available borehole image logs helped extend the analysis beyond individual wells to a field scale evaluation. Three analysis methods were developed to progress with the study: a favored drilling direction map, a Reservoir Property Filter, and crossplotting for multiple reservoir properties to gauge well performance. Results showed linear, nonlinear, and multidimensional relationships. The findings will be used to guide future HW drilling optimization, support dynamic modeling, and improve the model’s predictability for effective reservoir management.