Limited Site Data Research Articles

Multi-Lateral Well Productivity Evaluation Based on Three-Dimensional Heterogeneous Model in Nankai Trough, Japan

Widely employed in hydrate exploitation, the single well method is utilized to broaden the scope of hydrate decomposition. Optimizing the well structure and production strategy is necessary to enhance gas recovery efficiency. Complex wells represented by the multilateral wells have great application potential in hydrate mining. This study focused on the impact of multilateral well production methods on productivity, taking the Nankai Trough in Japan as the study area. The spatial distribution of physical parameters such as porosity, permeability, and hydrate saturation in the Nankai Trough has significant heterogeneity. For model accuracy, the Sklearn machine learning and Kriging interpolation methods were used to construct a three-dimensional heterogeneous geological model to describe the structure and physical property parameters in the study area of the hydrate reservoir. The numerical simulation model was solved using the TOUGH + Hydrate program and fitted with the measured data of the trial production project to verify its reliability. Finally, we set the multilateral wells for hydrate high saturation area to predict the gas and water production of hydrate reservoir with different exploitation schemes. The main conclusions are as follows: ① The Sklearn machine learning and Kriging interpolation methods can be used to construct a three-dimensional heterogeneous geological model for limited site data, and the fitting effect of the heterogeneous numerical simulation model is better than that of the homogeneous numerical simulation model. ② The multilateral well method can effectively increase the gas production rate from the hydrate reservoir compared with the traditional single well method by approximately 8000 m3/day on average (approximately 51.8%). ③ In the high saturation area, the number of branches of the multilateral well were set to 2, 3, and 4, and the gas production rate was increased by approximately 51.8%, 52.5%, and 53.5%. Considering economic consumption, the number of branching wells should be set at 2–3 in the same layer.

Environmental contours for wind-resistant bridge design in complex terrain

Accurate estimation of the extreme wind fields is crucial for long-span bridge design. The current practice is focused on estimating the extreme mean wind speed, neglecting the inherent uncertainty in the turbulence model parameters. However, full-scale measurements on bridges show that such uncertainties are significant and should be considered in design. Here, the environmental contour method (ECM) is used to obtain long-term extreme wind fields considering uncertainties from the mean wind speed, turbulence intensities and spectral parameters measured at the Sulafjord Bridge site. Design contours of combinations of wind field parameters are obtained for target return periods of 4, 50 and 100 years. The contours are based on a proposed probabilistic modeling strategy that combines hindcast mesoscale simulations and field measurements. The contour estimates are also compared with state-of-the-art design values from the design recommendations. It is concluded that the environmental contours provide a more complete and yet intuitive description of the wind field at the bridge site compared to the current design methodology. The ECM is found suitable for obtaining design wind fields at new long-span bridge sites as it makes use of the limited site data more efficiently and it is still easy-to-use for the practicing engineer.

Contamination Assessment and Site-Management Tool (CAST): A Browser-Based Tool for Site Assessment.

Groundwater dependency is increasing globally, while millions of potentially contaminated sites are yet to be characterized for contamination levels. In particular, groundwater contamination due to light nonaqueous phase liquids (LNAPLs) continues to be a global challenge. Mathematical approaches (i.e., analytical, semi-analytical, empirical, numerical) are preferred for an initial site assessment to circumvent the high characterization costs and limited site data availability. However, the site-specific nature of contamination restricts the generalization of any single approach. Hence, the requirement is for an easy-to-use computing interface that provides site-specific data management, the selection and use of multiple-model interfaces for computing, and site characterization, with extension for the latest models as they become available. This work provides one such interface called CAST or Contamination Assessment and Site-management Tool. CAST is an open-source browser-based (online/offline) tool that provides an interface for six different analytical models (e.g., BIOSCREEN-AT), a MODFLOW based numerical model, and two empirical models (including a hybrid numerical-analytical model). Additionally, CAST includes interfaces for site data management, their evaluation, and scenario-based modeling. CAST's development is in a modular format, which simplifies the addition of new computing or data interfaces. Furthermore, the entire code-base of CAST is based on open-source (dominantly Python programming) libraries and standards. This further simplifies the modification or extension of this tool. This paper introduces CAST, its different computing, and data management interfaces and provides examples of the tool's functionality primarily for the initial evaluation of contaminated sites.

Variability response function approach for foundation reliability

This paper explores the applicability of variability response functions to nonlinear soil–structure interaction problems, focusing on the impacts of spatially variable soil properties on foundation reliability regarding the settlement response. An estimation scheme is proposed to obtain the response functions, which involves a periodic function to approximate the relationship between foundation response and phase angles representing the soil variability patterns. Using a single set of realizations, the response function approach enables the evaluation of foundation reliability under various spatial variability patterns, including different autocovariance distances in three dimensions and the rotated anisotropy features of soil variations. This leads to significant reductions in computational demands compared to previous attempts of random field modelling, which often involved individual Monte Carlo simulations for each combination of spatial variability parameters. The proposed approach is applied to both shallow foundation and piled foundation cases, illustrating its range of applicability. For linear-elastic systems, the approach is shown to be effective for various coefficients of variation in soil variability. For elastic–plastic pile group analyses, the approach leads to efficient evaluation of the statistics of average and differential settlements of the pile group, both of which compare favourably with conventional random field simulation techniques. Since it does not require multiple random field realizations, the approach is particularly efficient in identifying the worst-case scenario of autocovariance distances that corresponds to the largest uncertainty in foundation response. This can become a useful tool for conservative reliability assessments under a project setting, since site-specific estimates of random field parameters are often imprecise due to limited site data.

Normalising domestic space heating demand using post hoc models

Current evidence suggests that the energy performance gap between predicted and actual use of energy in buildings is significantly weighted towards under prediction and can be as high as 200%. High-quality modelled and actual data are needed to ensure like for like comparisons when investigating the energy performance gap. Internal temperature ( ti) normalisation is a key process to ensure like for like comparisons but is often hampered by the lack of the original model due to the time lag between design, construction and occupancy. Here, we demonstrate the use of models created after data collection – i.e. post hoc – as a substitute for original models in evaluating the energy performance gap. The robustness of the internal temperature normalisation factor ( fti) is tested using measured data from 20 Passivhaus homes. The data from each home are inputted into 10 Passive House Planning Package and 10 Standard Assessment Procedure models with highly different domestic and non-domestic building configurations, creating 400 model variants. Each variant is further split into four cases of varying internal gains and solar radiation creating a total of 1600 variants. Results demonstrate that fti is resilient to differences in building configuration, solar radiation levels and varying internal gains (SEM < 0.02). Even though SEM increases when measured internal temperatures are below base assumptions, the impact of this error on the computed space heating demand is at most 4%. This suggests that post hoc models can be a substitute for actual models in evaluating the energy performance gap and that limited site data can still yield robust results. Practical application: Identifying the causes of the energy performance gap (the difference between modelled and measure energy demand) is complex. Normalising space heating demand for internal temperatures means that some differences between modelled and actual space heating demand can be accounted for. Building models such as Passive House Planning Package (PHPP) and Standard Assessment Procedure (SAP) are readily available and allow variations in climate and temperature data to be inputted. This research demonstrates that in practice any PHPP and SAP model can be used for normalisation, not just one that is building specific and that some parameters (internal temperature) are more important than others. This provides a simple and easily accessible approach to temperature normalisation that can be applied by industry to domestic dwellings.

Simulating CO2 Injection and Storage with Limited Site Data: the Utility of a Variably Complex Modeling Approach

A semi-analytical model for simulating injection of an immiscible fluid into a water-filled reservoir is developed which approximates the effects of horizontal injection wells, impermeable fault segments, and permeability anisotropy on phase saturation and fluid pressure. The modeling approach is based upon (1) an analytic element model for single-phase flow associated with specified flux, specified pressure, and impermeable line-segment elements within a reservoir of uniform thickness and porosity, (2) an analytical solution to the one-dimensional Buckley-Leverett equation for immiscible displacement of one fluid by another in porous media, subject to relative permeability functions dependent on fluid saturation, and (3) mapping of the Buckley-Leverett solution onto the two- dimensional flow field using particle tracking. Correction of the computed single-phase pressure distribution behind the fluid displacement front for two-phase flow is accomplished using a heuristic model. Application of the model to a proposed geological CO2 storage system, characterized by an injection zone that is proximally cut by extensions of a regional fault system, include assessments of the impact of permeability, anisotropy, and other reservoir characteristics on fluid pressure distributions (and, by extension, the potential for induced seismicity resulting from a reduction in effective stress).

A regression-based approach for estimating primary and secondary particulate matter intake fractions.

One of the common challenges for life cycle impact assessment and risk assessment is the need to estimate the population exposures associated with emissions. The concept of intake fraction (a unitless term representing the fraction of material or its precursor released from a source that is eventually inhaled or ingested) can be used when limited site data are available or the number of sources to model is large. Although studies have estimated intake fractions for some pollutant-source combinations, there is a need to quickly and accurately estimate intake fractions for sources and settings not previously evaluated. It would be expected that limited source or site information could be used to yield intake fraction estimates with reasonable accuracy. To test this theory, we developed regression models to predict intake fractions previously estimated for primary fine particles (PM2.5) and secondary sulfate and nitrate particles from power plants and mobile sources in the United States. Our regression models were able to predict pollutant-specific intake fractions with R2 between 0.53 and 0.86 and equations that reflected expected relationships (e.g., intake fraction increased with population density, stack height influenced the intake fraction of primary but not secondary particles). Further analysis would be needed to generalize beyond this case study and construct models applicable across source categories and settings, but our analysis demonstrates that inclusion of a limited number of parameters can significantly reduce the uncertainty in population-average exposure estimates.

Modelling plant and soil water dynamics in semi-arid ecosystems with limited site data

The processes and mechanisms involved in the soil moisture balance of semi-arid ecosystems are discussed. A model of water dynamics (WATDYN) is developed for estimating plant available soil moisture (PAM) on particular sites. Potentially the model could be applied anywhere in the savanna regions of the world, using a minimum of readily available site data and standard weather records. It calculates water distribution in the soil profile and models water uptake using a modified Penman-Monteith equation involving separate calculations of soil evaporation and transpirational loss from each soil layer. Default data are provided where site data are unavailable. Vegetation is modelled only to account for radiation interception and for resistances to transpiration and evaporation. Growth is calculated on the basis of transpiration efficiency (adjusted for temperature, vapour pressure deficit, soil fertility and the time of the year) and death as a function of temperature, vapour pressure deficit, water stress and the amount of green biomass. Dead biomass is reduced as a function of soil moisture, temperature and the amount of litter. Maximum leaf biomass of woody plants is considered to be constant from year to year.

Christchurch seismic hazard pilot study

A pilot zoning study has been carried out for ground shaking hazard in the city of Christchurch, using the grade-3 procedures of the draft manual on seismic zonation for geotechnical hazards, being developed by Technical Committee TC-4 of the ISSMFE. Because of limited site data, we were not able to produce a complete zoning map for the city, but ground motions were estimated at six distinct sites for which borehole data was available, and this provided a good test for the procedures of the manual. The city of Christchurch is situated on nearly 1 km of volcanic rock and alluvial sediments overlying greywacke basement, on the edge of the main seismic region of New Zealand. In addition to being an interesting site from the point of view of ground shaking, there are also liquefaction and slope stability hazards in the alluvial and beach sands found throughout the city, and in the recent loess deposits mantling the adjacent Port Hills. In the pilot study of ground shaking hazard, a seismicity model for the central South Island region published recently by Elder et al. (1991) was combined with the attenuation model of Kawashima et al. (1984) recommended in the draft manual, to estimate rock motion at Christchurch, described by its acceleration response spectrum. Transfer functions were computed for the site response to estimate motions at the six selected sites using the Thomson-Haskell method. The results were highly sensitive to details of. the upper 30 m or so of the soil profile. In the local context, the large disparity between our estimates of ground shaking at Christchurch and those implicit in the draft revision of NZS 4203 are disturbing. According to our study the draft code underestimates shaking by about a factor of two or more.