Subsurface Changes Research Articles

The Role of Subsurface Changes and Environmental Factors in Shaping Urban Heat Islands in Southern Xinjiang

The urban heat island (UHI) effect is one of the most prominent surface climate changes driven by human activities. This study examines the UHI characteristics and influencing factors in the Southern Xinjiang urban agglomeration using MODIS satellite data combined with observational datasets. Our results reveal a significant increase in impervious surfaces in the region between 1995 and 2015, with the most rapid expansion occurring from 2010 to 2015. This urban expansion is the primary driver of changes in UHI intensity. The analysis from 2000 to 2015 shows substantial spatial variation in UHI effects across cities. Hotan recorded the highest annual average daytime UHI intensity of 3.7 °C, while Aksu exhibited the lowest at approximately 1.6 °C. Daytime UHI intensity generally increased during the study period, with the highest intensities observed in the summer. However, nighttime UHI trends varied across cities, with most showing an increase in intensity. Temperature, precipitation, and aerosol optical depth (AOD) were identified as the main factors influencing annual average daytime UHI intensity, while PM10 concentration showed a weak and inconsistent correlation with UHI intensity, varying by city and season.

Rayleigh wave ellipticity from ambient noise: A practical method for monitoring seismic velocity variations in the near-surface

This study explores the feasibility and limitations of using Rayleigh wave (Rg) ellipticity for noise-based seismic monitoring at near-surface depths (4–70 m). We use the degree of polarization (DOP) method to extract the Rayleigh wave ellipticity from seismic noise recordings, employing normalized cross-correlation and cross-covariance coefficients to quantify ellipticity variations over time. Synthetic models and field data from three distinct case studies—Garner Valley, California; Riotinto mine, Spain; and the 2011 submarine volcanic eruption on El Hierro Island, Canary Islands—validate our approach. In these field applications, our method effectively tracks the seasonality of the shallow groundwater levels in Garner Valley, monitors pore pressure variations at the tailings dam of Riotinto mine, and detects volcanic induced changes on El Hierro, demonstrating robust performance even with variable noise sources. Our results indicate that Rayleigh wave ellipticity is a versatile tool for subsurface monitoring, capable of detecting velocity changes across a broad depth range. Our methodology represents a new independent and non-interferometric approach that enhances the detection of subsurface changes while improving resolution and exploration depth in seismic monitoring techniques.

Cross‐equalization for time‐lapse sparker seismic data

AbstractTime‐lapse seismic data processing is an important technique for observing subsurface changes over time. The conventional time‐lapse seismic exploration has been conducted using a large‐scale exploration system. However, for efficient monitoring of shallow subsurface, time‐lapse monitoring based on the small‐scale exploration system is required. Small‐scale exploration system using a sparker source offers high vertical resolution and cost efficiency, but it faces challenges, such as inconsistent waveforms of sparker sources, inaccurate positioning information and a low signal‐to‐noise ratio. Therefore, this study proposes a data processing workflow to preserve the signal and enhance the repeatability of small‐scale time‐lapse seismic data acquired using a sparker source. The proposed workflow has three stages: pre‐stack, post‐stack and machine learning–based data processing. Conventional seismic data processing methods were applied to enhance the quality of the sparker seismic data during the pre‐stack data processing stage. In the post‐stack processing stage, the positions and energy correction were performed, and the machine learning–based data processing stage attenuated random noise and applied a matched filter. The data processing was performed using only the seismic signals recorded near the seafloor, and the results confirmed the improvement in the repeatability of the entire seismic profile, including that of the target area. According to the repeatability quantification results, the predictability increased and the normalized root mean square decreased during data processing, indicating improved repeatability. In particular, the repeatability of the data was greatly improved through vertical correction, energy correction and matched filtering approaches. The processing results demonstrate that the data processing method proposed in this study can effectively enhance the repeatability of high‐resolution time‐lapse seismic data. Consequently, this approach could contribute to a more accurate understanding of temporal changes in subsurface structure and material properties.

Development of a subsurface monitoring system for land subsidence hazard in the Bandung basin: a laboratory prototype

Abstract Land subsidence is a global environmental hazard posed by urban area worldwide, causing degradation in environmental quality and leads to further disasters such as increased flood risk, contamination risk, and infrastructure damages. Anthropogenic causes, such as groundwater extraction and building weight, cause high land subsidence rates. The behaviour of the subsurface under the influence of anthropogenic causes must be well understood to mitigate this problem. Conventional subsurface monitoring is robust and costly. In this case, we aim to first develop a versatile and low-cost subsurface monitoring prototype for land subsidence at a laboratory scale using a model box. Methods employed were constructing an experiment model box, developing the monitoring system, and trial experiments in the laboratory. The sensors are linear vertical displacement transducer, potentiometer, water level and pressure sensors. The monitoring system uses Arduino microcontroller to convert sensors inputs to desirable outputs and a logger to record the real-time data and transmit it to personal computer in the laboratory. Land subsidence in the Gedebage area in Bandung basin was taken as a model case. The model box was filled with soil from Gedebage, Bandung. A scenario of exploitation of confined groundwater and weight of building was applied for the model case. The results show that the laboratory prototype can monitor the subsurface changes due to the applied anthropogenic forces. In the case of Bandung soil, groundwater exploitation did not immediately cause subsidence instantaneously. There is a time delay between the drawdown of groundwater level and the subsequent vertical deformation. The rate of subsidence varies spatially inside the tank, the largest is close to the pump well and surface loads. A maximum of 2.88 mm subsidence over 663 days was recorded following 1 m groundwater drawdown. This information asserts the importance of long-time monitoring in subsidence areas.

Imaging Biomarkers of Oral Dysplasia and Carcinoma Measured with In Vivo Endoscopic Optical Coherence Tomography.

Optical coherence tomography is a noninvasive imaging technique that provides three-dimensional visualization of subsurface tissue structures. OCT has been proposed and explored in the literature as a tool to assess oral cancer status, select biopsy sites, or identify surgical margins. Our endoscopic OCT device can generate widefield (centimeters long) imaging of lesions at any location in the oral cavity-but it is challenging for raters to quantitatively assess and score large volumes of data. Leveraging a previously developed epithelial segmentation network, this work develops quantifiable biomarkers that provide direct measurements of tissue properties in three dimensions. We hypothesize that features related to morphology, tissue attenuation, and contrast between tissue layers will be able to provide a quantitative assessment of disease status (dysplasia through carcinoma). This work retrospectively assesses seven biomarkers on a lesion-contralateral matched OCT dataset of the lateral and ventral tongue (40 patients, 70 sites). Epithelial depth and loss of epithelial-stromal boundary visualization provide the strongest discrimination between disease states. The stroma optical attenuation coefficient provides a distinction between benign lesions from dysplasia and carcinoma. The stratification biomarkers visualize subsurface changes, which provides potential for future utility in biopsy site selection or treatment margin delineation.

Reversible Intercalation of Organic Solvents in Graphite and Its Hindrance by a Strongly Adsorbing Supramolecular Monolayer

AbstractAt elevated temperatures, the prototypical organic solvents used to study the self‐assembly of supramolecular monolayers at liquid–solid interfaces alter a graphite substrate by intercalation. As a consequence, less strongly bound supramolecular monolayers become thermodynamically unstable, as probed by scanning tunneling microscopy. Complementary characterization by atomic force microscopy, confocal Raman spectroscopy and low energy electron microscopy consistently points to subsurface changes in the top few layers of the graphite substrate due to solvent intercalation. High‐temperature annealing at 900 °C in the vacuum restores the adsorption properties of the graphite substrates, indicating a high activation energy for deintercalation. However, strongly adsorbing hydrogen‐bonded monolayers of trimesic acid inhibit solvent intercalation and thus protect the graphite substrate. Mildly solvent‐intercalated graphite may prove useful as an easily prepared graphitic material with further weakened adsorption properties.

Neotectonic impact on drainage development in the Eastern Himalayan foreland basin

The present study intends to divulge the complex drainage evolution in connection to neotectonic controls focusing the Jaldhaka and Raidak River interfluve on the eastern Himalayan Foreland Basin (HFB). It involves analysing the surface and sub-surface changes in the fluvial system's evolution with field and geospatial evidence bearing geomorphic markers, sediment analogy and channel morphological properties. The channel orientation, planimetry and the channel longitudinal process anomaly were attributed solely from the geospatial perspective as surface evidence of neotectonic controls. The results unveil an intense neotectonic control on channel development–from structurally guided channel avulsion that shaped the presently active course of the Torsa River to deformation-guided channel morphological changes. Moreover, relatively higher deflection angles, intense channel sinuosity and tight meandering bends forming along the structural elements symptomizes the structure-controlled drainage development in recent times. Furthermore, sediment analogy from deep well logs and shallow subsurface trenches was analysed to obtain subsidence-driven fluvial sequences and geochronology of sedimentary deformation in channel beds and floodplains. The Optically Stimulated Luminescence (with fading correction) technique-based determination of shallow sub-surface sediment's age indicates occurrences of palaeoseismic events between 1.6 ka (±0.1 ka) and 1.35 ka (±0.2 ka) as well as between 1.35 ka (±0.2 ka) and 1.14 ka (±0.1 ka) had resulted in channel bed sagging while stress impacted the formation of syn-sedimentary folding. The palaeoseismic events that led to relative subsidence are evident in upward sediment stacking (channel fill) sequences being observed at multiple trenches. The deep sub-surface staking of channel floor deposition lenses is also evident of basin subsidence that influenced channel oscillations of reoccupation type.

Corrigendum: Dynamic subsurface changes on El Hierro and La Palma during volcanic unrest revealed by temporal variations in seismic anisotropy patterns

Corrigendum: Dynamic subsurface changes on El Hierro and La Palma during volcanic unrest revealed by temporal variations in seismic anisotropy patterns

Future directions in geological research impacting renewable energy and carbon capture: A synthesis of sustainable management techniques

Geological research plays a pivotal role in shaping the future of renewable energy and carbon capture initiatives, offering insights into sustainable management techniques. This review synthesizes the future directions in geological research that impact renewable energy and carbon capture, focusing on sustainable management techniques. Future geological research will increasingly focus on enhancing the integration of renewable energy sources into existing energy systems. This includes the development of innovative geological mapping techniques to identify and characterize renewable energy resources with greater precision, aiding in the selection of optimal sites for energy production. Additionally, there will be a growing emphasis on utilizing geological data to assess the feasibility of carbon capture and storage (CCS) projects, particularly in volcanic regions, where the unique geological characteristics offer potential for efficient carbon sequestration. Another key aspect of future geological research is the advancement of monitoring and modeling techniques to evaluate the long-term performance and environmental impact of renewable energy and CCS projects. This includes the use of advanced geophysical and geochemical methods to monitor subsurface changes associated with energy extraction and carbon storage, ensuring the effectiveness and safety of these practices. Furthermore, future research will explore the potential of geological formations, such as deep saline aquifers and depleted oil and gas reservoirs, for large-scale carbon storage. This will involve developing strategies to enhance storage capacity and mitigate the risk of CO2 leakage, contributing to the sustainable management of carbon emissions. In conclusion, future geological research will play a critical role in advancing renewable energy and carbon capture technologies, offering sustainable management techniques that are essential for addressing climate change. By focusing on innovative mapping, monitoring, and modeling approaches, researchers can pave the way for a more sustainable energy future.

Bayesian variational time-lapse full waveform inversion

SUMMARY Time-lapse seismic full-waveform inversion (FWI) provides estimates of dynamic changes in the Earth’s subsurface by performing multiple seismic surveys at different times. Since FWI problems are highly non-linear and non-unique, it is important to quantify uncertainties in such estimates to allow robust decision making based on the results. Markov chain Monte Carlo (McMC) methods have been used for this purpose, but due to their high computational cost, those studies often require a pre-existing accurate baseline model and estimates of the locations of potential velocity changes, and neglect uncertainty in the baseline velocity model. Such detailed and accurate prior information is not always available in practice. In this study we use an efficient optimization method called stochastic Stein variational gradient descent (sSVGD) to solve time-lapse FWI problems without assuming such prior knowledge, and to estimate uncertainty both in the baseline velocity model and the velocity change over time. We test two Bayesian strategies: separate Bayesian inversions for each seismic survey, and a single joint inversion for baseline and repeat surveys, and compare the methods with standard linearized double difference inversion. The results demonstrate that all three methods can produce accurate velocity change estimates in the case of having fixed (exactly repeatable) acquisition geometries. However, the two Bayesian methods generate significantly more accurate results when acquisition geometries changes between surveys. Furthermore, joint inversion provides the most accurate velocity change and uncertainty estimates in all cases tested. We therefore conclude that Bayesian time-lapse inversion using a joint inversion strategy may be useful to image and monitor subsurface changes, in particular where variations in the results would lead to different consequent decisions.

Feasibility of reservoir monitoring in the Groningen gas field using ghost reflections from seismic interferometry

SUMMARY Seismic interferometry (SI) retrieves new seismic responses, for example reflections, between either receivers or sources. When SI is applied to a reflection survey with active sources and receivers at the surface, non-physical (ghost) reflections are retrieved as well. Ghost reflections, retrieved from the correlation of two primary reflections or multiples from two different depth levels, are only sensitive to the properties in the layer that cause them to appear in the result of SI, such as velocity, density and thickness. We aim to use these ghost reflections for monitoring subsurface changes, to address challenges associated with detecting and isolating changes within the target layer in monitoring. We focus on the feasibility of monitoring pore-pressure changes in the Groningen gas field in the Netherlands using ghost reflections. To achieve this, we utilize numerical modelling to simulate scalar reflection data, deploying sources and receivers at the surface. To build up subsurface models for monitoring purposes, we perform an ultrasonic transmission laboratory experiment to measure S-wave velocities at different pore pressures. Applying SI by autocorrelation to the modelled data sets, we retrieve zero-offset ghost reflections. Using a correlation operator, we determine time differences between a baseline survey and monitoring surveys. To enhance the ability to detect small changes, we propose subsampling the ghost reflections before the correlation operator and using only virtual sources with a complete illumination of receivers. We demonstrate that the retrieved time differences between the ghost reflections exhibit variations corresponding to velocity changes inside the reservoir. This highlights the potential of ghost reflections as valuable indicators for monitoring even small changes. We also investigate the effect of the sources and receivers’ geometry and spacing and the number of virtual sources and receivers in retrieving ghost reflections with high interpretability resolution.

Dynamic subsurface changes on El Hierro and La Palma during volcanic unrest revealed by temporal variations in seismic anisotropy patterns

Active hotspot volcanism is the surface expression of ongoing dynamic subsurface changes, such as the generation, transport, and stalling of magmas within the upper mantle and crust. Magmatic influx and migration affects local stress patterns in the crust and lithospheric mantle, which influences seismic anisotropy. A better understanding of those patterns helps improve robustness of models forecasting the likelihood of an eruption and prolonged seismicity, with detailed studies being required to observe the significant variations that can occur on small spatial and temporal scales. Here, we investigate seismic anisotropy before, during and after volcanic eruptions. We use local seismicity around El Hierro and La Palma, the two westernmost islands in the Canaries and sites of the most recent volcanic eruptions in the archipelago. We obtained 215 results in El Hierro during and after the 2011/2012 eruption with five three-component broadband seismic stations and 908 results around the 2021 eruption in La Palma with two three-component broadband stations. On La Palma, the majority of seismicity and splitting results are recorded during the eruption and simultaneous deflation of the island. Seismicity locations do not change significantly and fast shear wave polarisation direction is mostly constant, but some variation can be attributed to changes in the magmatic plumbing system. On El Hierro, the general radial pattern reflects stresses induced by the overall uplift of the island during multiple magma intrusion events. Temporal subsets reveal significant variations in location and depth of the events, as well as significant variations in fast polarisation direction caused by ongoing dynamic changes of under- and overpressurisation. An increase of results starting in 2018 hints towards renewed subsurface activity within deeper parts of the plumbing system, affecting the rate of overall seismicity but not any vertical movement of the island.

Visualizing small-scale subsurface NH3 and pH dynamics surrounding nitrogen fertilizer granules and impacts on nitrification activity

In agricultural soils, nitrogen (N) fertilizer is typically applied as ammonium salts or urea, and undergoes microbially mediated oxidation. However, insights regarding substrate concentrations nitrifiers are exposed to in the zones immediately surrounding N fertilizer granules remain unexamined, as well as how this affects the activity or inhibition of nitrifier groups adapted to different ranges of ammonia (NH3) concentrations. To examine millimeter scale changes in soil chemistry after sub-surface fertilizer granule application with high spatiotemporal resolution, we applied a newly developed NH3 and pH planar optical sensor (optode) system. With this system, we visualized in situ subsurface NH3 production, diffusion, and associated pH shifts in an agricultural soil following the application (from 5 min up to 65.5 h) of ammonium chloride (NH4Cl) or urea granules in a laboratory study. Ammonia from both NH4Cl and urea granules diffused up to 1.5 and 2 cm and reached maximum concentrations of >49 and >130 ppmv, respectively. Spatially informed destructive subsampling (0.5–2 cm from granules) revealed that nitrate accumulation was greatest closest (0.5–1 cm) to the ammonium chloride granules, while nitrite was not detected. In contrast, urea application resulted in both nitrite and nitrate accumulation, with the highest concentrations detected furthest (1.5–2 cm) from urea granules. Urea hydrolysis also caused a significant localized pH increase, while ammonium chloride caused a circular elevated pH zone migrating outwards leaving a decreased pH at the center. Transcription of the ammonia-oxidizing bacterial amoA gene was highest in areas furthest (1.5–2 cm) from the urea granules, while there were no significant differences in amoA transcription with increasing distance from the NH4Cl granules. Ammonia-oxidizing archaea and comammox amoA transcripts were not detected. This study is the first to directly visualize small-scale subsurface changes in NH3 concentration and pH after fertilizer granule application and relate these to nitrification activity.

Detection of Low-Velocity Layer Using Passive Surface-Wave Data and Deep Learning: An Application in The Urban Area of Hangzhou, China

Passive surface-wave methods using dense seismic arrays have gained growing attention in near-surface high-resolution imaging in urban environments. Deep learning (DL) can release a tremendous workload brought by dense seismic arrays. We presented a case study of shear-wave velocity (Vs) structure imaging in the Hangzhou urban area (eastern China) using DL inversion. Noise data were recorded by dense linear arrays with approximately 5 m spacing deployed along two crossing roads for investigating the top 80 m of the subsurface. Phase-velocity dispersion curves are extracted from virtual shot gathers using multichannel analysis of surface waves. We divided the area where the low-velocity layer (LVL) may exist into three layers with a thickness of 5 m. We gave the four layers weak constraints to generate training dataset and adopted a convolutional neural network to directly invert fundamental-mode Rayleigh-wave phase velocity for 1D Vs models. To improve the accuracy, we further applied the sensitivities to weight the loss function in DL inversion. The obtained pseudo-2D Vs profiles correspond to the velocities estimated from logging data and previous survey. The well-trained neural network successfully identified that the LVL is located at 50-60 m deep. And this network was also achieved accurately the inversion of a dense seismic network nearby. The results of this survey demonstrate the accuracy and efficiency of delineating near-surface structures from traffic-induced noise using the DL technique, which has great potential for monitoring subsurface changes in urban areas.

Amplified Subsurface Signals of Ocean Acidification

AbstractWe evaluate the impact of anthropogenic carbon (Cant) accumulation on multiple ocean acidification (OA) metrics throughout the water column and across the major ocean basins using the GLODAPv2.2016b mapped product. OA is largely considered a surface‐intensified process caused by the air‐to‐sea transfer of Cant; however, we find that the partial pressure of carbon dioxide gas (pCO2), Revelle sensitivity Factor (RF), and hydrogen ion concentration ([H+]) exhibit their largest responses to Cant well below the surface (>100 m). This is because subsurface seawater is usually less well‐buffered than surface seawater due to the accumulation of natural carbon from organic matter remineralization. pH and aragonite saturation state (ΩAr) do not exhibit spatially coherent amplified subsurface responses to Cant accumulation in the GLODAPv2.2016b mapped product, though nonlinear characteristics of the carbonate system work to amplify subsurface changes in each OA metric evaluated except ΩAr. Regional variability in the vertical gradients of natural and anthropogenic carbon create regional hot spots of subsurface intensified OA metric changes, with implications for vertical shifts in biologically relevant chemical thresholds. Cant accumulation has resulted in subsurface pCO2, RF, and [H+] changes that significantly exceed their respective surface change magnitudes, sometimes by >100%, throughout large expanses of the ocean. Such interior ocean pCO2 changes are outpacing the atmospheric pCO2 change that drives OA itself. Re‐emergence of these waters at the sea surface could lead to elevated CO2 evasion rates and reduced ocean carbon storage efficiency in high‐latitude regions where waters do not have time to fully equilibrate with the atmosphere before subduction.

Superpixel-based change detection for GPR time-lapse slices using fuzzy c-means and the Markov random field method

Ageing and complex underground utility infrastructure present a significant challenge for modern society, requiring long-term monitoring and maintenance to prevent economic and social costs associated with infrastructure degradation and failure. In this study, we proposed an unsupervised superpixel-based change-detection method using ground-penetrating radar time-lapse slices combining fuzzy c-means and the Markov random field model to investigate an invisible subsurface change due to buried void using time-series measurements. First, simple linear iterative clustering was applied to the difference image, which was generated using paired time-lapse images after intensity registration to create different scales superpixel maps. Then, fuzzy c-means clustering was used to generate superpixel-based change maps. Finally, the Markov random field model was used to integrate the information of adjacent neighbourhoods in three dimensions to iteratively refine the change map. We designed two underground cavities (one representing shallow local voids and the other representing voids near pipeline networks) to verify the capability and adaptability of the proposed method. The experimental results demonstrate the feasibility of the method, with F1-scores of 0.82, 0.69, 0.69, and 0.65 and kappa coefficients of 0.81, 0.69, 0.68, and 0.64. Our method represents a significant contribution to the field of GPR-based change detection and has the potential to improve the long-term monitoring and maintenance of complex underground utility infrastructure.

The subsurface lesion in erosive tooth wear

ObjectivesThis study compared the surface change on natural and polished enamel exposed to a joint mechanical and chemical wear regimen. MethodsHuman enamel samples were randomly assigned to natural (n = 30) or polished (n = 30) groups, subjected to erosion (n = 10, 0.3% citric acid, 5 min), abrasion (n = 10, 30 s), or a combination (n = 10). Wear in the form of step height was measured with a non-contact profilometer, and surface changes were inspected with SEM on selected sections. Data was normalised and underwent repeated measures MANOVA, accounting for substrate and erosive challenge as independent variables, with Bonferroni correction for significant post hoc interactions. ResultsAfter four cycles, polished samples had mean step heights of 3.08 (0.40) μm after erosion and 4.08 (0.37) μm after erosion/abrasion. For natural samples, these measurements were 1.52 (0.22) μm and 3.62 (0.39) μm, respectively. Natural surfaces displayed less wear than polished surfaces under erosion-only conditions (p<0.0001), but the difference disappeared with added abrasion. SEM revealed a shallow subsurface layer for polished surfaces and natural ones undergoing only erosion. However, natural surfaces exposed to both erosion and abrasion showed deeper subsurface changes up to 50 µm. ConclusionNatural enamel, when exposed to erosion alone, showed less wear and minimal subsurface alterations. But with added abrasion, natural enamel surfaces saw increased wear and notable subsurface changes compared to polished ones. Clinical SignificanceThe pronounced subsurface lesions observed on eroded/abraded natural enamel surfaces highlight how combined wear challenges may accelerate tooth tissue loss.

3D DC inversion, visualization, and processing of dense time-lapse data in fine domains applied to remediation monitoring

Using electrical direct-current (DC) data to monitor the subsurface is an efficient solution for observing changes in the shallow subsurface. Recent advances in instrumentation enable the acquisition of large data sets over 3D domains in a reasonable time. We have developed an inversion approach capable of handling very large amounts of data on a finely discretized domain, which enables the delivery of time-lapse results of dense data acquisitions in a feasible time and with high resolution. To spatially represent 3D DC data, a visualization method is introduced that formally generalizes the focusing point of a common pseudosection in three dimensions. The method physically describes subsurface properties for simple geologic scenarios. In addition, the focusing points are used to design our 3D measuring protocol. We develop a DC data processing scheme using the full time-domain induced polarization (IP) waveform data by applying two novel physics-based criteria that enforce charge buildup and steady state. These criteria are tested on DCIP field data and find that 98% of the filtered DC data have less than 1% relative error. The 3D visualization method and inversion algorithm are evaluated on synthetic scenarios of 3D DC dense borehole data. Then, we indicate time-lapse results of DC field data acquired at an uncontaminated site where a remediation agent was injected at depth. The data are acquired with a new DCIP instrument capable of measuring dense data sets at fast acquisition times. Accounting for DCIP data acquisition, signal processing, and 3D inversion of 60,000 DC measurements, our results locate in 14 h the 3D spread of the remediation agent in a [Formula: see text] volume.

Modelling the Influence of Erosive Fluidization on the Morphology of Fluid Flow and Escape Structures

Focused fluid flow through sub-seafloor pipes and chimneys, and their seafloor manifestations as pockmarks, are ubiquitous. However, the dynamics of flow localization and evolution of fluid escape structures remain poorly understood. Models based on geomechanical mechanisms like hydro-fracturing and porosity wave propagation offer some useful insights into fluid flow and escape dynamics, but face limitations in capturing features like mobilized granular matter, especially in the upper sediment layers where the link between fracture and pockmark is not always clear. Here, we propose a mathematical model based on the multiphase theory of porous media, where changes in subsurface and seafloor morphology are resolved through seepage-induced erosion, fluidization, transport, and re-deposition of granular material. Through simulation of an idealized scenario of gas escape from overpressured shallow gas reservoir, we demonstrate that our model can capture flow localization and formation of pipes, chimneys, and pockmarks. Our simulations show (1) formation of conical focused-flow conduits with a brecciated core and annular gas channels; (2) pockmarks of W and ring shapes; and (3) pulsed release of gas. Sediment erodibility and flow anisotropy control the morphology of focused fluid flow and escape structures, while permeability shows negligible impact. While the geological setting for this study is theoretical, we show that our results have real-world analogs.

Characteristics and attribution analysis of runoff and sediment evolution in the Wei River mainstream, China

Abstract This study evaluates the characteristics of river runoff and sediment changes in the Wei River mainstream over the past 50 years based on runoff and sediment data and meteorological data from 1971 to 2020 at the Huaxian hydrological station in the lower reaches of the Wei River. The main research methods are the Mann–Kendall method, wavelet analysis, cross-wavelet analysis, and cumulative curve method. The results show that there is no significant decreasing trend and abrupt change in runoff volume in recent years, the decreasing trend of sediment transport is obvious, and the abrupt change occurs around 2006. The dominant periodicity of runoff is 12–13a, and the dominant periodicity of sediment transport is 5a. There is only a significant resonance periodicity of 3–5a in 1980–1990, which is roughly a positive correlation. The runoff–sediment series can be divided into four time periods, and the reasons for the change in the runoff–sediment relationship are different in each time period. The precipitation factor has a slightly greater impact on runoff and a weak impact on sediment transport, with contribution rates of 21.2 and 7.6%. Human activities such as subsurface changes and water conservancy construction have a greater impact on runoff and sediment load, with contribution rates of 78.8 and 92.4%.