Physics

A family of constitutive models for mine cemented backfill is presented. Four formulas for the density- and pressure-dependency of elastic moduli, five formulas for the density- and pressure-dependency of friction angle and four formulas for the age-dependency of the elastic moduli and effective cohesion are incorporated into an isotropic hypoelasticity with Mohr-Coulomb perfect plasticity framework and implemented in PLAXIS as a user-defined material model. This family includes the standard Mohr-Coulomb, Bolton, Leps, Barton and Hoek- Brown models as trivial cases when both nonlinear elasticity and age-dependency are switched off. In this paper, the formulation of the models is introduced, the basis of the numerical implementation is outlined, and a case history of the application to the cemented backfill of a sublevel stoping mine is presented as an example.

A geothermal well doublet, designed for two primary aims of research and commercial heat supply, is planned to be constructed on the campus of Delft University of Technology. The plans include a comprehensive research programme, including installation of a wide range of instruments alongside a comprehensive logging and coring programme and an extensive surface monitoring network. The wells will be cored, with samples from all representative geological units down to the reservoir. An extensive suite of well-logs is planned to provide detailed information on the properties of the various units. Fibre-optic cables will be installed in both wells all the way down to the reservoir section, which is anticipated to be at 2200m, in the Lower Cretaceous Delft Sandstone. The Delft sandstone is well-known as a reservoir rock for natural gas in the West Netherlands Basin. The wells will be operated by a commercial entity, but the infrastructure is designed and explicitly installed as a research infrastructure. As such it will become part of the European EPOS (European Plate Observing System, this https URL), such that accessibility and data availability will not be limited to TU Delft researchers. The university has made a decision in principle to start drilling no later than 2020.

Structural seismic interpretation and quantitative characterization are historically intertwined processes. The latter provides estimates of properties of the subsurface which can be used to aid structural interpretation alongside the original seismic data and a number of other seismic attributes. In this work, we redefine this process as a inverse problem which tries to jointly estimate subsurface properties (i.e., acoustic impedance) and a piece-wise segmented representation of the subsurface based on user-defined macro-classes. By inverting for the quantities simultaneously, the inversion is primed with prior knowledge about the regions of interest, whilst at the same time it constrains this belief with the actual seismic measurements. As the proposed functional is separable in the two quantities, these are optimized in an alternating fashion, where each subproblem is solved using a Primal-Dual algorithm. Subsequently, each class is used as input to a workflow which aims to extract the perimeter of the detected shapes and to produce unique horizons. The effectiveness of the proposed method is illustrated through numerical examples on synthetic and field datasets.

The enhanced oil recovery technique of low-salinity (LS) water flooding is a topic of substantial interest in the petroleum industry. Studies have shown that LS brine injection can increase oil production relative to conventional high-salinity (HS) brine injection, but contradictory results have also been reported and an understanding of the underlying mechanisms remains elusive. We have recently developed a steady-state pore network model to simulate oil recovery by LS brine injection in uniformly wetted pore structures (Watson et al., Transp. Porous Med. 118, 201-223, 2017). We extend this approach here to investigate the low-salinity effect (LSE) in heterogeneously wetted media. We couple a model of capillary force-driven fluid displacement to a novel tracer algorithm and track the salinity front in the pore network as oil and HS brine are displaced by injected LS brine. The wettability of the pore structure is modified in regions where water salinity falls below a critical threshold, and simulations show that this can have significant consequences for oil recovery. For networks that contain spanning clusters of both water-wet and oil-wet (OW) pores prior to flooding, our results demonstrate that the OW pores contain the only viable source of incremental oil recovery by LS brine injection. Moreover, we show that a LS-induced increase in microscopic sweep efficiency in the OW pore fraction is a necessary, but not sufficient, condition to guarantee additional oil production. Simulations suggest that the fraction of OW pores in the network, the average network connectivity and the initial HS brine saturation are key factors that can determine the extent of any improvement in oil recovery in heterogeneously wetted networks following LS brine injection. This study highlights that the mechanisms of the LSE can be markedly different in uniformly wetted and non-uniformly wetted porous media.

Over the past decades, the Groningen Gas Field (GGF) has been increasingly faced by induced earthquakes resulting from gas production. The seismic monitoring network at Groningen has been recently densified to improve the seismic network performance, resulting in increasing amounts of seismic data. Although traditional automated event detection techniques generally are successful in detecting events from continuous data, its detection success is challenged in cases of lower signal-to-noise ratios. The data stream coming from these networks has initiated specific interest in neural networks for automated classification and interpretation. Here, we explore the feasibility of neural networks in detecting the occurrence of seismic events. For this purpose, a three-layered feedforward neural network was trained using public data of a seismic event in the GGF obtained from the Royal Netherlands Meteorological Institute (KNMI) data portal. The first arrival times and duration of earthquake waveforms determined by KNMI for a subset of the station data, were used to detect the arrival times and event duration for the other uninterpreted station data. Subsequently various attributes were used as input for the neural network, that were based on different short term averaging/long term averaging (STA/LTA) and frequency sub-band settings. Using these input data, the network's parameters were iteratively improved to maximize its capability in successfully discriminating seismic events from noise and determine the event duration. Results show an increase of 65 % in accurately detecting seismic events and determining their duration as compared to the reference method. This clears the way for improved interpretation of signal waveforms and automated seismic event classification in the Groningen area.

The moment tensors of a large portion of deep earthquakes show apparent non-double-couple (non-DC) components. Previously, the observed apparent non-DC values in deep earthquakes have been attributed to different mechanisms such as complex source processes or complicated source medium structures. In this paper, we focused on evaluating the second mechanism. We investigated the effect of slab heterogeneity, supra-slab anisotropic structure, intra-slab weakly anisotropic structure (e.g., the purported existence of the metastable olivine wedge), and non-uniform station coverage, on the non-DC radiation patterns of deep earthquakes using our 3-dimensional elastic finite-difference modeling and full-waveform inversion of moment tensors. We found that these investigated issues cannot cause the observed non-double-couple radiation patterns and the in-situ structure with strong S-wave anisotropy near to the earthquake focus is the simplest way to account for the apparent non-DC components in the radiation patterns of deep earthquakes.

Analyzing paradoxes is interesting and instructive. Sometimes the analysis leads to non-trivial results. This methodological note sets out a paradox arising in the theory of propagation of electromagnetic waves in moving plasmas. The paradox is interesting in itself, and, generally speaking, it should be taken into account when analyzing geoelectromagnetic waves. The paradox is as follows: contrary to expectations, the group velocity of the waves is the same in the comoving and laboratory frames of reference. The condition for the appearance of the paradox is the quadratic dependence of the frequency on the wave number. A paradoxical property manifests itself in the theory of the propagation of radio waves (in particular, whistling atmospherics), Langmuir waves and Alfvén waves. From a cognitive point of view, it is interesting that the paradox can be traced in relation to de Broglie waves. An explanation of the paradox is proposed. Keywords: group velocity, moving plasma, Doppler Effect, dispersion, longitudinal waves, transverse waves.

Non-invasive surface wave methods have become a popular alternative to traditional invasive forms of site-characterization for inferring a site's subsurface shear wave velocity (Vs) structure. The advantage of surface wave methods over traditional forms of site characterization is that measurements made solely at the ground surface can be used routinely and economically to infer the subsurface structure of a site to depths of engineering interest (20-50 m), and much greater depths (>1 km) in some special cases. However, the quantification and propagation of uncertainties from surface wave measurements into the Vs profiles used in subsequent engineering analyses remains challenging. While this has been the focus of much work in recent years, and while considerable progress has been made, no approach for doing so has been widely accepted, leading analysts to either address the propagation of uncertainties in their own specialized manner or, worse, to ignore these uncertainties entirely. In response, this paper presents an easy-to-implement, effective, and verifiable method for developing uncertainty-consistent Vs profiles from inversion of surface wave dispersion data. We begin by examining four approaches presented in the literature for developing suites of Vs profiles meant to account for uncertainty present in the measured dispersion data. These methods are shown to be deficient in three specific ways. First, all approaches are shown to be highly sensitive to their many user-defined inversion input parameters, making it difficult/impossible for them to be performed repeatedly by different analysts. Second, the suites of inverted Vs profiles, when viewed in terms of their implied theoretical dispersion data, are shown to significantly underestimate the uncertainty present in the experimental dispersion data, though some may appear satisfactory when viewed purely qualitatively...

Loss of circulation while drilling is a challenging problem that may interrupt operations, reduce efficiency, and may contaminate the subsurface. When a drilled borehole intercepts conductive faults or fractures, lost circulation manifests as a partial or total escape of drilling, workover, or cementing fluids, into the surrounding rock formations. Loss control materials (LCM) are often used in the mitigation process. Understanding the fracture effective hydraulic properties and fluid leakage behavior is crucial to mitigate this problem. Analytical modeling of fluid flow in fractures is a tool that can be quickly deployed to assess lost circulation and perform diagnostics, including leakage rate decline, effective fracture conductivity, and selection of the LCM. Such models should be applicable to Newtonian and non-Newtonian yield-stress fluids, where the fluid rheology is a nonlinear function of fluid flow and shear stress. In this work, a new semi-analytical solution is developed to model the flow of non-Newtonian drilling fluid in a fractured medium. The solution model is applicable for various fluid types exhibiting yield-power-law (Herschel-Bulkley). We use high-resolution finite-element simulations based on the Cauchy equation to verify our solutions. We also generate type-curves and compare them to others in the literature. We demonstrate the applicability of the proposed model for two field cases encountering lost circulations. To address the subsurface uncertainty, we combine the developed solutions with Monte-Carlo and generate probabilistic predictions. The solution method can estimate the range of fracture conductivity, parametrized by the fracture hydraulic aperture, and time-dependent fluid loss rate that can predict the cumulative volume of lost fluid. The proposed approach is accurate and efficient enough to support decision-making for real-time drilling operations.

We report on slow earthquakes in Northern Cascadia, and show that continuous seismic energy in the subduction zone follows specific patterns leading to failure. We rely on machine learning models to map characteristic energy signals from low-amplitude seismic waves to the timing of slow slip events. We find that patterns in seismic energy follow the 14-month slow slip cycle. Our results point towards a recurrent build-up in seismic energy as the fault approaches failure. This behavior shares a striking resemblance with our previous observations from slow slips in the laboratory.