Controls on deep critical zone architecture: a historical review and four testable hypotheses

The base of Earth's critical zone (CZ) is commonly shielded from study by many meters of overlying rock and regolith. Though deep CZ processes may seem far removed from the surface, they are vital in shaping it, preparing rock for infusion into the biosphere and breaking Earth materials down for transport across landscapes. This special issue highlights outstanding challenges and recent advances of deep CZ research in a series of articles that we introduce here in the context of relevant literature dating back to the 1500s. Building on several contributions to the special issue, we highlight four exciting new hypotheses about factors that drive deep CZ weathering and thus influence the evolution of life‐sustaining CZ architecture. These hypotheses have emerged from recently developed process‐based models of subsurface phenomena including: fracturing related to subsurface stress fields; weathering related to drainage of bedrock under hydraulic head gradients; rock damage from frost cracking due to subsurface temperature gradients; and mineral reactions with reactive fluids in subsurface chemical potential gradients. The models predict distinct patterns of subsurface weathering and CZ thickness that can be compared with observations from drilling, sampling and geophysical imaging. We synthesize the four hypotheses into an overarching conceptual model of fracturing and weathering that occurs as Earth materials are exhumed to the surface across subsurface gradients in stress, hydraulic head, temperature, and chemical potential. We conclude with a call for a coordinated measurement campaign designed to comprehensively test the four hypotheses across a range of climatic, tectonic and geologic conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

Mechanisms linking active rock glaciers and impounded surface water formation in high‐mountain areas

Rock glaciers are slowly flowing mixtures of debris and ice occurring in mountains. They can represent a reservoir of water, and melting ice inside them can affect surface water hydrochemistry. Investigating the interactions between rock glaciers and water bodies is therefore necessary to better understand these mechanisms. With this goal, we elucidate the hydrology and structural setting of a rock glacier–marginal pond system, providing new insights into the mechanisms linking active rock glaciers and impounded surface waters. This was achieved through the integration of waterborne geophysical techniques (ground penetrating radar, electrical resistivity tomography and self‐potentials) and heat tracing. Results of these surveys showed that rock glacier advance has progressively filled the valley depression where the pond is located, creating a dam that could have modified the level of impounded water. A sub‐surface hydrological window connecting the rock glacier to the pond was also detected, where an inflow of cold and mineralised underground waters from the rock glacier was observed. Here, greater water contribution from the rock glacier occurred following intense precipitation events during the ice‐free season, with concomitant increasing electrical conductivity values. The outflowing dynamic of the pond is dominated by a sub‐surface seepage where a minor fault zone in bedrock was found, characterised by altered and highly‐fractured rocks. The applied approach is evaluated here as a suitable technique for investigating logistically‐complex hydrological settings which could be possibly transferred to wider scales of investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

不同结构深度神经网络的时间域航空电磁数据成像性能分析

时间域航空电磁系统采样密集,数据量大,所以在该领域较为实用的数据处理方法主要为一维反演和电阻率成像法。笔者从成像问题出发,建立了庞大的数据模型训练集,研究并分析了不同结构的神经网络的成像精度。通过对比分析测试结果,获得了在一定条件下适用于航空电磁成像的最优网络模型结构,包含其神经元个数和层数等信息。本文采用早停法训练神经网络,压制数据中噪声对成像结果的影响。     

Deep neural network application for 4D seismic inversion to changes in pressure and saturation: Optimizing the use of synthetic training datasets

In this work, we tackle the challenge of quantitative estimation of reservoir dynamic property variations during a period of production, directly from four-dimensional seismic data in the amplitude domain. We employ a deep neural network to invert four-dimensional seismic amplitude maps to the simultaneous changes in pressure, water and gas saturations. The method is applied to a real field data case, where, as is common in such applications, the data measured at the wells are insufficient for properly training deep neural networks, thus, the network is trained on synthetic data. Training on synthetic data offers much freedom in designing a training dataset, therefore, it is important to understand the impact of the data distribution on the inversion results. To define the best way to construct a synthetic training dataset, we perform a study on four different approaches to populating the training set making remarks on data sizes, network generality and the impact of physics-based constraints. Using the results of a reservoir simulation model to populate our training datasets, we demonstrate the benefits of restricting training samples to fluid flow consistent combinations in the dynamic reservoir property domain. With this the network learns the physical correlations present in the training set, incorporating this information into the inference process, which allows it to make inferences on properties to which the seismic data are most uncertain. Additionally, we demonstrate the importance of applying regularization techniques such as adding noise to the synthetic data for training and show a possibility of estimating uncertainties in the inversion results by training multiple networks.     

A high-precision time–frequency analysis for thin hydrocarbon reservoir identification based on synchroextracting generalized S-transform

Improving the seismic time–frequency resolution is a crucial step for identifying thin reservoirs. In this paper, we propose a new high-precision time–frequency analysis algorithm, synchroextracting generalized S-transform, which exhibits superior performance at characterizing reservoirs and detecting hydrocarbons. This method first calculates time–frequency spectra using generalized S-transform; then, it squeezes all but the most smeared time–frequency coefficients into the instantaneous frequency trajectory and finally obtains highly accurate and energy-concentrated time–frequency spectra. We precisely deduce the mathematical formula of the synchroextracting generalized S-transform. Synthetic signal examples testify that this method can correctly decompose a signal and provide a better time–frequency representation. The results of a synthetic seismic signal and real seismic data demonstrate that this method can identify some reservoirs with thincknesses smaller than a quarter wavelength and can be successfully applied for hydrocarbon detection. In addition, examples of synthetic signals with different levels of Gaussian white noise show that this method can achieve better results under noisy conditions. Hence, the synchroextracting generalized S-transform has great application prospects and merits in seismic signal processing and interpretation.     

Strong slope-aspect control of regolith thickness by bedrock foliation

The porous near-surface layer of the Earth's crust – the critical zone – constitutes a vital reservoir of water for ecosystems, provides baseflow to streams, guides recharge to deep aquifers, filters contaminants from groundwater, and regulates the long-term evolution of landscapes. Recent work suggests that the controls on regolith thickness include climate, tectonics, lithology, and vegetation. However, the relative paucity of observations of regolith structure and properties at landscape scales means that theoretical models of critical zone structure are incompletely tested. Here we present seismic refraction and electrical resistivity surveys that thoroughly characterize subsurface structure in a small catchment in the Santa Catalina Mountains, Arizona, USA, where slope-aspect effects on regolith structure are expected based on differences in vegetation. Our results show a stark contrast in physical properties and inferred regolith thickness on opposing slopes, but in the opposite sense of that expected from environmental models and observed vegetation patterns. Although vegetation (as expressed by normalized difference vegetation index [NDVI]) is denser on the north-facing slope, regolith on the south-facing slope is four times thicker (as indicated by lower seismic velocities and resistivities). This contrast cannot be explained by variations in topographic stress or conventional hillslope morphology models. Instead, regolith thickness appears to be controlled by metamorphic foliation: regolith is thicker where foliation dips into the topography, and thinner where foliation is nearly parallel to the surface. We hypothesize that, in this catchment, hydraulic conductivity and infiltration capacity control weathering: infiltration is hindered and regolith is thin where foliation is parallel to the surface topography, whereas water infiltrates deeper and regolith is thicker where foliation intersects topography at a substantial angle. These results suggest that bedrock foliation, and perhaps by extension sedimentary layering, can control regolith thickness and must be accounted for in models of critical zone development. © 2020 John Wiley & Sons, Ltd.     

Impact of three-dimensional attitude variations of an unmanned aerial vehicle magnetometry system on magnetic data quality

Optically pumped vapour magnetometers have an orientation dependency in measuring the scalar component of the ambient magnetic field which leads to challenges for integration with mobile platforms. Quantifying the three-dimensional attitude variations (yaw, pitch and roll) of an optically pumped vapour magnetometer, while in-flight and suspended underneath a rotary unmanned aerial vehicle, aids in the successful development of reliable, high-resolution unmanned aerial vehicle magnetometry surveys. This study investigates the in-flight three-dimensional attitude characteristics of a GEM Systems Inc. GSMP-35U potassium vapour magnetometer suspended 3 m underneath a Dà-Jiāng Innovations S900 multi-rotor unmanned aerial vehicle. A series of unmanned aerial vehicle-borne attitude surveys quantified the three-dimensional attitude variations that a simulated magnetometer payload experienced while freely (or semi-rigidly) suspended underneath the unmanned aerial vehicle in fair weather. Analysis of the compiled yaw, pitch and roll data resulted in the design of a specialized semi-rigid magnetometer mount, implemented to limit magnetometer rotation about the yaw axis. A subsequent unmanned aerial vehicle-borne magnetic survey applying this specialized mount resulted in more than 99% of gathered GSMP-35U magnetic data being within industry standards. Overall, this study validates that maintaining magnetometer attitude variations within quantified limits (±5° yaw, ±10° pitch and roll) during flight can yield reliable, continuous and high-resolution unmanned aerial vehicle-borne magnetic measurements.     

Energy of acoustic signals in a borehole

In the present article, the dependencies of the acoustic signal total energy and the energies of the wave packets of different types of the waves on the elastic parameters and permeability of rocks have been studied. We have considered traditional logging tools containing acoustical monopole source. Calculations were performed in a frequency range of dozens of kilohertz, typical for acoustic well logging. It was shown that in a typical high-velocity formation (v_s > v_f, where v_s and v_f are the velocities of the shear wave in the rock and of the compressional wave in the borehole fluid, respectively), the pseudo-Rayleigh waves, whose elastic properties depend mainly on the shear modulus of the rock, contributed significant energy to the total signal energy in the borehole. The energies of different wave packets depend on the permeability in different ways. The greatest sensitivity to permeability change has been shown by the acoustic signal total energy and the energy of the low-velocity part of the pseudo-Rayleigh wave packet. The theoretical analysis was illustrated by real sonic log data.     

From Grain to Floodplain: Evaluating heterogeneity of floodplain hydrostatigraphy using sedimentology,geophysics, and remote sensing

Stratigraphy is a fundamental component of floodplain heterogeneity and hydraulic conductivity and connectivity of alluvial aquifers, which affect hydrologic processes such as groundwater flow and hyporheic exchange. Watershed-scale hydrological models commonly simplify the sedimentology and stratigraphy of floodplains, neglecting natural floodplain heterogeneity and anisotropy. This study, conducted in the upper reach of the East River in the East River Basin, Colorado, USA, combines point-, meander-, and floodplain-scale data to determine key features of alluvial aquifers important for estimating hydrologic processes. We compare stratigraphy of two meanders with disparate geometries to explore floodplain heterogeneity and connectivity controls on flow and transport. Meander shape, orientation, and internal stratigraphy affected residence time estimates of laterally exchanged hyporheic water. Although the two meanders share a sediment source, vegetation, and climate, their divergent river migration histories resulted in contrasting meander hydrofacies. In turn, the extent and orientation of these elements controlled the effective hydraulic conductivity and, ultimately, estimates of groundwater transport and hyporheic residence times. Additionally, the meanders’ orientation relative to the valley gradient impacted the hydraulic gradient across the meanders—a key control of groundwater velocity. Lastly, we combine our field data with remotely sensed data and introduce a potential approach to estimate key hydrostratigraphic packages across floodplains. Prospective applications include contaminant transport studies, hyporheic models, and watershed models. © 2019 John Wiley & Sons, Ltd.     

Intra-survey reservoir fluctuations – implications for quantitative 4D seismic analysis

During the time taken for seismic data to be acquired, reservoir pressure may fluctuate as a consequence of field production and operational procedures and fluid fronts may move significantly. These variations prevent accurate quantitative measurement of the reservoir change using 4D seismic data. Modelling studies on the Norne field simulation model using acquisition data from ocean-bottom seismometer and towed streamer systems indicate that the pre-stack intra-survey reservoir fluctuations are important and cannot be neglected. Similarly, the time-lapse seismic image in the post-stack domain does not represent a difference between two states of the reservoir at a unique base and monitor time, but is a mixed version of reality that depends on the sequence and timing of seismic shooting. The outcome is a lack of accuracy in the measurement of reservoir changes using the resulting processed and stacked 4D seismic data. Even for perfect spatial repeatability between surveys, a spatially variant noise floor is still anticipated to remain. For our particular North Sea acquisition data, we find that towed streamer data are more affected than the ocean-bottom seismometer data. We think that this may be typical for towed streamers due to their restricted aperture compared to ocean-bottom seismometer acquisitions, even for a favourable time sequence of shooting and spatial repeatability. Importantly, the pressure signals on the near and far offset stacks commonly used in quantitative 4D seismic inversion are found to be inconsistent due to the acquisition timestamp. Saturation changes at the boundaries of fluid fronts appear to show a similar inconsistency across sub-stacks. We recommend that 4D data are shot in a consistent manner to optimize aerial time coverage, and that additionally, the timestamp of the acquisition should be used to optimize pre-stack quantitative reservoir analysis.