Synthetic Modeling Research Articles

RNA secondary structure packages evaluated and improved by high-throughput experiments.

Despite the popularity of computer-aided study and design of RNA molecules, little is known about the accuracy of commonly used structure modeling packages in tasks sensitive to ensemble properties of RNA. Here, we demonstrate that the EternaBench dataset, a set of more than 20,000 synthetic RNA constructs designed on the RNA design platform Eterna, provides incisive discriminative power in evaluating current packages in ensemble-oriented structure prediction tasks. We find that CONTRAfold and RNAsoft, packages with parameters derived through statistical learning, achieve consistently higher accuracy than more widely used packages in their standard settings, which derive parameters primarily from thermodynamic experiments. We hypothesized that training a multitask model with the varied data types in EternaBench might improve inference on ensemble-based prediction tasks. Indeed, the resulting model, named EternaFold, demonstrated improved performance that generalizes to diverse external datasets including complete messenger RNAs, viral genomes probed in human cells and synthetic designs modeling mRNA vaccines.

Curve Flow-duration-Frequency. The flood modelling regime of the Wadi Mazafran catchment in the north of Algeria

Synthetic modelling of the flood regime is based on the overall knowledge of the hydrological regime in a catchment. The Flow-duration-Frequency (QdF) modelling is used to combine three parameters characterising flood with its mean or exceeded flow, its characteristic duration, and occurrence frequency. Which of these can be established locally at the extreme mean volume flow rates of a catchment reference hydrometric station? The determination of the reference QdF model in mean (volume) and exceeded flows requires two characteristics reflecting the flood regime in a catchment. The first is the characteristic flood duration and the second is the 10-year quantile of the annual maximum instantaneous flow. The comparison of the local situation to the reference QdF models enables to develop the final QdF model of the catchment and therefore the baseline QdF for exceeded and synthetic mono-frequency hydrographs. These are essential components in the study of flood risk mapping and the estimation of the instantaneous peak distribution from mean daily streamflow series.

Resistivity imaging of river embankments: 3D effects due to varying water levels in tidal rivers

AbstractElectrical resistivity tomography (ERT) has seen increased use in the monitoring the condition of river embankments, due to its spatial subsurface coverage, sensitivity to changes in internal states, such as moisture content, and ability to identify seepage and other erosional process with time‐lapse ERT. Two‐dimensional ERT surveys are commonly used due to time and site constraints, but they are often sensitive to features of anomalous resistivity proximal to the survey line, which can distort the resultant inversion as a three‐dimensional (3D) effect. In a tidal embankment, these 3D effects may result from changing water levels and river water salinities. ERT monitoring data at Hadleigh Marsh, UK, showed potential evidence of 3D effects from local water bodies. Synthetic modelling was used to quantify potential 3D effects on tidal embankments. The modelling shows that a 3D effect in a tidal environment occurs (for the geometries studied) when surveys are undertaken at high water levels and at distances less than 4.5 m from the electrode array with 1 m spacing. The 3D effect in the modelling is enhanced in brackish waters, which are common in tidal environments, and with larger electrode spacing. Different geologies, river water compositions, and proximities to the model parameters are expected to induce a varied 3D effect on the ERT data in terms of magnitude, and these should be considered when surveying to minimize artefacts in the data. This research highlights the importance of appropriate geoelectrical measurement design for tidal embankment characterization, particularly with proximal and saline water bodies.

Methodologies for Synthetic Spatial Building Stock Modelling: Data-Availability-Adapted Approaches for the Spatial Analysis of Building Stock Energy Demand

Buildings are responsible for around 30 to 40% of the energy demand and greenhouse gas (GHG) emissions in European countries. Building stock energy models (BSEMs) are an established method to assess the energy demand and environmental impact of building stocks. Spatial analysis of building stock energy demand has so far been limited to cases where detailed, building specific data is available. This paper introduces two approaches of using synthetic building stock energy modelling (SBSEM) to model spatially distributed synthetic building stocks based on aggregate data. The two approaches build on different types of data that are implemented and validated for two separate case studies in Ireland and Austria. The results demonstrate the feasibility of both approaches to accurately reproduce the spatial distribution of the building stocks of the two cases. Furthermore, the results demonstrate that by using a SBSEM approach, a spatial analysis for building stock energy demand can be carried out for cases where no building level data is available and how these results may be used in energy planning.

Subsurface structure of the proposed Sirente meteorite crater: insights from ERT synthetic modelling

The Sirente main crater is a ≈ 130 m wide, in plan view droplet-shaped depression with an elevated rim, surrounded by 30 smaller depressions. It was proposed to be of meteorite impact origin. Given the age of formation in the 3rd to 5th centuries A.D., the inferred catastrophic origin was related to the celestial sign (“Chi Rho”) said to have been seen by Emperor Constantine in 312 A.D. and suggested to have changed the course of both Roman and Christian history. However, the meteoritic origin is not yet confirmed. This paper presents new results from synthetic modelling of Electric Resistivity Tomography field data collected at the Sirente main crater which provide further clues around the controversy of its origin. This study arises from the need to validate the observed structural features which include possible upturned strata (i.e., overturning of strata below impact crater rims) and compaction-fissure-like features below and just outside the crater rim, well-developed “breccia lens”, as well as an ejecta layer, and provide key indicators for objective and quantitative interpretation of the measured resistivity pattern. The results from this study are consistent with the hypothesis of a small impact crater in a low-strength target, with a relatively shallow apparent crater and do not support other proposed mechanisms of formation such as karst, mud volcano or merely anthropogenic origin.

Simulation of Heat Flow in a Synthetic Watershed: Lags and Dampening across Multiple Pathways under a Climate-Forcing Scenario

Although there is widespread agreement that future climates tend toward warming, the response of aquatic ecosystems to that warming is not well understood. This work, a continuation of companion research, explores the role of distinct watershed pathways in lagging and dampening climate-change signals. It subjects a synthetic flow and transport model to a 30-year warming signal based on climate projections, quantifying the heat breakthrough on a monthly time step along connected pathways. The system corresponds to a temperate watershed roughly 27 km on a side and consists of (a) land-surface processes of overland flow, (b) infiltration through an unsaturated zone (UZ) above an unconfined sandy aquifer overlying impermeable bedrock, and (c) groundwater flow along shallow and deep pathlines that converge as discharge to a surface-water network. Numerical simulations show that about 40% of the warming applied to watershed infiltration arrives at the water table and that the UZ stores a large fraction of the upward-trending heat signal. Additionally, once groundwater reaches the surface-water network after traveling through the saturated zone, only about 10% of the original warm-up signal is returned to streams by discharge. However, increases in the simulated streamflow temperatures are of similar magnitude to increases at the water table, due to the addition of heat by storm runoff, which bypasses UZ and groundwater storage and counteracts subsurface dampening. The synthetic modeling method and tentative findings reported here provide a potential workflow for real-world applications of climate-change modeling at the full watershed scale.

Primary Multiparametric Quantitative Brain MRI: State-of-the-Art Relaxometric and Proton Density Mapping Techniques.

This review on brain multiparametric quantitative MRI (MP-qMRI) focuses on the primary subset of quantitative MRI (qMRI) parameters that represent the mobile ("free") and bound ("motion-restricted") proton pools. Such primary parameters are the proton densities, relaxation times, and magnetization transfer parameters. Diffusion qMRI is also included because of its wide implementation in complete clinical MP-qMRI application. MP-qMRI advances were reviewed over the past 2 decades, with substantial progress observed toward accelerating image acquisition and increasing mapping accuracy. Areas that need further investigation and refinement are identified as follows: (a) the biologic underpinnings of qMRI parameter values and their changes with age and/or disease and (b) the theoretical limitations implicitly built into most qMRI mapping algorithms that do not distinguish between the different spatial scales of voxels versus spin packets, the central physical object of the Bloch theory. With rapidly improving image processing techniques and continuous advances in computer hardware, MP-qMRI has the potential for implementation in a wide range of clinical applications. Currently, three emerging MP-qMRI applications are synthetic MRI, macrostructural qMRI, and microstructural tissue modeling.

A SYNTHETIC PRECIPITATION MODEL TO DETERMINE THE USAGE OF THE DISTRIBUTION OF RAIN AS A DATA INPUT IN CALCULATING THE DESIGN FLOOD

In calculating the design-flood discharge, engineers often use the frequency-distribution analysis of rainfall data as the basis for obtaining the magnitude of the design flood. The distribution of rain stations is an important factor in determining the distribution of regional rainfall; however, not all catchments have sufficient rain stations to represent the distribution of precipitation in a watershed. This results in a flood hydrograph—obtained using a rainfall–runoff model that is based on the calculation of the estimated rainfall—with a low level of correlation with the observed hydrograph. This research aims to set up a synthetic rain station that corrects the difference between the simulated hydrograph and observed hydrograph to achieve a better correlation level. Usually, researchers use the available rain stations for analyzing the design rainfall and design flood; however, in this research, a synthetic rain station has been built. Rainfall–runoff modeling methods for ungauged catchments (UCs), i.e., watersheds without observation stations, are widely available. Each method has different parameters to determine the unit hydrograph in a watershed. During the development of rainfall–runoff models at UCs, the precipitation in the upstream of a watershed is often assumed to be uniform, but it is not the case. The methodology used in this study collects hourly rainfall data from the ARR and hourly flood-discharge data from the AWLR in one catchment, then calculates the Thiessen coefficient before and after the set up of the synthetic rain station, and finally, calculates the rainfall at the synthetic rain station by trial and error. From the results of the synthetic rainfall modeling, the equation for the synthetic rainfall is obtained:ArRR=(-0.127A-0.260FB-0.307Re+1.227Q+0.51)/(C.K_Thiessen ) with a correlation coefficient of R = 0.818 in a watershed area below 300 km2.

Synthetic modeling and field GPR survey to understand the near-surface deformation induced by coseismic groundwater dynamics following the 2019 Mirpur earthquake in Pakistan

The Mirpur earthquake of Mw 5.8 on 24 September 2019 severely damaged villages in the epicentral area. The earthquake-triggered ground dynamics produced widespread liquefaction features on the surface (e.g., fractured road structure and sand boils) and in the shallow subsurface (e.g., elevated groundwater table, fractures, and sand dikes). Due to complexity of liquefaction-induced deformation and timing of field surveys, the structural and hydrogeologic features that develop in the near surface during seismic events are often poorly resolved on ground-penetrating-radar (GPR) profiles. To track and delineate the internal architecture and coseismic changes in groundwater levels and/or pressures due to liquefaction, a GPR survey was carried out soon after the Mirpur earthquake. The sudden pore water pressure changes in the shallow aquifer system caused a rise in the water table via upward groundwater movement and fracturing followed by rapid infiltration. This cascade phenomenon has adverse effects on soil, water resources, civil infrastructure, and public health and safety. To better understand induced changes in the physical properties of road infrastructure and the shallow subsurface, we performed synthetic modeling of electromagnetic wave propagation by employing the finite-difference time-domain method. Based on the available information at multiple scales (borehole and geophysical), subsurface physical models representing the most common and important coseismic features were considered for synthetic modeling. Likewise, synthetic tests of paved road were conducted to simulate the radar response of structural discontinuities (fractures) developed at different angles. To validate synthetic results by identifying a similar dynamic response of the induced hydrogeologic changes in the form of coseismic liquefaction features, a field GPR survey was conducted. Our results clearly demonstrate that the GPR technique is a potential candidate for hydrogeophysical detection and characterization of features of interest in the case of paved roads as well as agricultural and residential areas. Additionally, the successful application of GPR proves it to be a cost-effective, high-resolution, and speedy tool for better assessment of hydrogeologic hazard, socioeconomic consequences, and mitigation in the Mirpur area. The proposed approach may find applications in other seismically active regions around the world.

Elastic Slab in Viscoelastic Mantle: Effects on Determining Megathrust Slip and Mantle Viscosity During Postseismic and Interseismic Phases

AbstractEarthquake‐cycle deformation at subduction zones is not only induced by cyclical faulting processes but also impacted by the Earth structure and rheology. Oversimplifying the first‐order Earth structure in models leads to biased estimations of fault kinematics and Earth rheology and hence misinterpretation of subduction‐zone dynamics. Here we first use synthetic models to investigate the impacts of an elastic slab on viscoelastic postseismic and interseismic deformation and on determining afterslip, locking distribution, and mantle viscosity. We confirm that the presence of a slab causes anchored viscous flow in the mantle wedge and less extensive viscoelastic deformation in the overriding plate than the depth‐dependent layered models without a slab during the interseismic and postseismic phases. By assuming the predicted viscoelastic deformation from the model with a slab as the synthetic true observations, layered models obtain a higher viscosity and more slip on the downdip of the seismogenic zone than the true model during both phases. These biased estimates are found varying with the displacement component, spatial and temporal coverages of the used observations. We then conduct two real‐world case studies at the Japan subduction zone and find that the layered model obtains the biased fault kinematics and mantle viscosity that are similar to the synthetic modeling results, indicating that the slab signature may have been observed in the geodetic data. Our findings highlight the importance of including a slab in modeling the earthquake‐cycle deformation and thoroughly exploring the sensitivities of surface deformation, especially the verticals, on the deep Earth structures.

Identification of Seismic Response to Aquifer System with A Synthetic Modelling Approach

The microseismic method is relatively new in groundwater exploration, especially in Indonesia. This study will examine the response of microseismic to groundwater aquifer systems. This study aims to analyze the response of seismic waves and to interpret the seismic wave response characteristics to the aquifer system model. The modeling of the aquifer system was carried out using seismic stratigraphy data. This data was used as input data to model the exposed HVSR curve using the Microtrem program in MATLAB. The study of physical parameters and supporting parameters of the aquifer layer and the air contained in it was carried out to support this modeling. The aquifer system modeling was carried out with various parameters, including saturation, porosity, and thickness of the aquifer layer. Furthermore, an analysis of the model is carried out to determine the response characteristics of the aquifer system to microseismic waves. The results show that the frequency range as a marker of the presence of the aquifer ranges from 2-4 Hz, which is determined by parameters within a specific value.

Magnetotelluric Investigations of the Kīlauea Volcano, Hawaii

AbstractIn 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the U.S. Geological Survey (USGS) Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kīlauea volcano in Hawaii using the magnetotelluric (MT) technique. The work was motivated by a desire to improve understanding of the magma reservoirs and conduits within Kīlauea and the East and Southwest Rift zones, which has implications for understanding Kīlauea's plumbing system. An improved understanding of the rift zones has implications in understanding large‐scale landslides that are generated in the Hilina Slump, which produce significant impacts on coastal communities. Up to eight stations operated simultaneously, with multiple remote reference sites, and data were processed using multi‐station robust processing techniques. In total, data were acquired at 70 sites over the Southwest and East rift zones. Good to excellent quality data were obtained even in the harshest conditions, such as those encountered on the fresh lava flows of the East Rift Zone, where electrical contact resistances are on the order of 100 kΩ. A three‐dimensional (3D) MT model study was done to guide interpretation of the observed MT measurements. Synthetic modeling demonstrates that conductive bodies in the upper 3 km can be spatially resolved where MT station sampling is good. Resistivity anomalies in the 3D inversions have a high degree of spatial correlation with previously published seismic velocity anomalies beneath Kīlauea. Melt fractions between 0.096 and 0.117 are calculated for the Kīlauea and Puʻuʻōʻō low resistivity anomalies, respectively.

Multi-scale GIS-synthetic hybrid approach for the development of commercial building stock energy model

For energy modelling of commercial building stock (CBS), several methodologies were developed focusing on technology alternatives and retrofits for climate change mitigation, but they often have limitations to involve a differentiated description of practices and policies across a range of scales and sectors. This paper presents a novel hybrid model by integrating spatial and synthetic modelling approaches to facilitate the concurrent consideration of multiple building-oriented elements. The model is further implemented on Japanese building stock to demonstrate multi-scale and long-term framework for energy modelling of CBS. The results indicate the following findings: the scale choice introduces significant variability in energy consumption estimation with a relative error of 10–17% mainly depending on building geometry and plug loads; the long-term model exhibits a higher scale-bounded uncertainty in terms of energy saving potential that varies by 2–3 times when a non-representative scale is applied; disregarding physical and technical factors results in a cumulative performance gap of up to 32%; and the accuracy and extent of the model across the stock are more sensitive to technical factors, such as building system stock dynamics and the heterogeneity of HVAC systems, than physical factors. The model provides a multi-tier framework using spatial intelligence building stock approach to develop long-term energy efficiency monitoring strategies for CBS.

Groundwater-level recovery following closure of open-pit mines

Open-pit mining has increased substantially over the past two decades. Many currently operating open-pit mines are facing the end of mine-life over the next few decades and, increasingly, focus is shifting towards mine-closure planning that provides evidence on available closure options under the given geological, hydro(geo)logical and climatic conditions. This study uses synthetic groundwater modelling to build basic process understanding of closure options and how these will determine the formation of pit lakes. This governs the long-term pit lake water quality and how postmining landscapes may be utilised. Simulations show that the recovery time of postmining groundwater levels increases with decreasing aquifer transmissivity. Final postmining water tables are predominantly controlled by the implemented mine closure options and climatic conditions. The most important decision is, thereby, whether to backfill the pit to above the water table or allow a pit lake to develop. Under moderately transmissive aquifer settings, backfilling of pits leads to rapidly rising groundwater levels within the first decade after mining, with water-table recoveries of above 70%. If mine voids remain unfilled, evaporation from the pit lake surface becomes a governing factor in determining whether the unfilled mine pit becomes a terminal sink for groundwater. Lake levels may remain subdued by several 10s of metres in arid to semiarid climates. If surplus surface water can be diverted into open pits, rapid filling can accelerate groundwater recovery of open pits in regions of low permeability. This is a less successful management option in transmissive aquifers.

Internal absorbing boundary conditions for closed-aperture wavefield decomposition in solid media with unknown interiors.

We present a method to create an internal numerical absorbing boundary within elastic solid media whose properties are largely unknown and use it to create the first wavefield separation method that retrieves all orders of outgoing elastic wavefield constituents for real data recorded on a closed free surface. The recorded data are injected into a numerical finite-difference (FD) simulation along a closed, transparent surface, and the new internal numerical absorbing boundary condition achieves high attenuation of the ingoing waves radiated from the injection surface. This internal wave absorption enables the data injection to radiate all outgoing waves for experimental domains that include arbitrary unknown scatterers in the interior. The injection-absorption-based separation scheme is validated using three-dimensional (3D) synthetic modeling and a real data experiment acquired using a 3D laser Doppler vibrometer on a granite rock. The wavefield separation method forms a key component of an elastic immersive wave experimentation laboratory, and the ability to numerically absorb ingoing scattered energy in an uncharacterized medium while still radiating the true outgoing energy is intriguing and may lead to other development and applications in the future.

Cost‐effective in‐mine seismic experiments to image platinum deposits and associated geological structures at Maseve platinum mine, South Africa

ABSTRACTThe detection of mineral deposits and their related geological structures is of great importance to the mining industry as structures (such as dykes and faults) can affect the safety, cost and efficiency of mining. With the goal of testing cost‐effective seismic methods for mineral exploration and mining, active and passive seismic experiments were conducted at Maseve platinum mine in the Bushveld Complex (South Africa) in 2020. The experiments involved surface‐passive (using 5 Hz wireless nodes; single vertical component) and in‐mine active reflection seismic surveys (using 4.5 Hz land streamer and 5 kg sledgehammer) to image geological structures and delineate economic platinum‐group elements bearing Merensky and Upper Group‐2 chromitite layers (known as reefs). This paper presents only the results from the in‐mine active seismic experiments. The in‐mine seismic surveys consisted of seven 2D reflection seismic profiles in the development tunnels, which were located ∼550 m below ground surface and a few tens of metres above known mineralizations: the Upper Group‐2 and Merensky Reef. The data were carefully processed to enhance the reflections and suppress noise generated by mine infrastructure (e.g., equipment and ventilation). We successfully imaged the Merensky Reef and Upper Group‐2 orebodies approximately 55 m and 124 m below the tunnel floor, respectively, and delineated faults and dykes that crosscut them. Furthermore, the seismic data reveal relatively strong amplitude and faulted reflections below the Upper Group‐2 that may represent deeper chromitite‐enriched orebodies. However, the economic value of these horizons can only be confirmed through drilling. The processed seismic data were combined with borehole data, synthetic modelling and geological models to constrain the interpretation. This study encourages the use of in‐mine seismics for future mineral exploration, mine development and planning.

Exploration of a Copper Ore Deposit in Elbistan/Turkey Using 2D Inversion of the Time-Domain Induced Polarization Data by Using Unstructured Mesh

We present the results of a direct current (DC) resistivity and time-domain induced polarization (TDIP) survey exploring a copper ore deposit in Elbistan/Turkey. The ore deposit is elongated below a valley and is of disseminated form with sulfide content. DC and IP data were acquired using the pole-dipole array on eight parallel profiles crossing the valley perpendicularly. The length of each profile was 300 m with an inter-profile distance of about 50 m. The data were interpreted by a newly developed 2D DC/TDIP inversion algorithm. The finite element algorithm uses a local smoothness constrained regularization on unstructured meshes. The finite element forward solution, as well as the inverse problem, is solved by an iterative preconditioned conjugate solver. The depth of investigation (DOI) was determined from cumulative sensitivities of the 2D inversion algorithm results. Because of the dissemination of the ore, the 2D inversion of the DC data was ambiguous: However, due to the sulfide content, a strong chargeability anomaly associated with the ore body was detected. We show that chargeability anomalies can generally be detected in the absence or presence of corresponding resistivity anomalies. This highly chargeable structure was confined in lateral direction. Although the lower boundary of the structure could not be resolved by the applied field set-up, a rough estimation of it could be derived at a depth of 90 m using synthetic modeling analyses. The 2D chargeability models are consistent with existing borehole information.

Nonlinear viscoelastic modeling of synthetic mooring lines

The study aims at improving the state of the art in predicting the dynamic behavior of synthetic mooring lines used in offshore floating structures. Current practices of employing linear or load-dependent stiffness model can lead to erroneous prediction of tensions in these lines, when nonlinear viscoelastic characteristics of the line material are important. State of the art empirical models utilize data from one of two experimental approaches: strain based, wherein stress is measured from the material deformations, and stress-based, when strain is recorded from the stress inputs. Common mooring solvers employ the stress-based approach, however, experiments needed to evaluate the material empirical coefficients are difficult to carry out for highly extensible synthetic ropes. To address these issues, this paper proposes a numerical inverting scheme to calculate the stress-based nonlinear viscoelastic properties using experimental data from strain-based tests. An open-source constitutive program (SYNCOM – A Nonlinear Synthetic Constitutive Modelling Tool) based on the strain-based semi-empirical model is developed and validated. Comparisons with published data on the behaviors of different materials subjected to various load types are well correlated. For a mooring case study, SYNCOM is integrated into the open-source lumped mass mooring software MoorDyn. Simulations of mooring tensions subjected to rapidly changing environmental conditions - mimicking the effects from 1) extreme coherent gust with direction change and 2) snap loads during survival storm - are investigated. Results show that without consideration of time-dependent effects, the predictions for mean load and mean amplitudes could lead to an overestimation ranging from 2.5% to 16%.

Synthetic and DFT Modeling Studies on Suzuki–Miyaura Reactions of 4,5-Dibromo-2-methylpyridazin-3(2H)-one with Ferrocene Boronates, Accompanied by Hydrodebromination and a Novel Bridge-Forming Annulation In Vitro Cytotoxic Activity of the Ferrocenyl–Pyridazinone Products

This paper presented the efficiency of different Pd-based catalytic systems in a series of SM reactions of 4,5-dibromo-2-methylpyridazin-3(2H)-one with ferroceneboronic acid, ferrocene-1,1′-diboronoc acid, and its bis-pinacol ester. In addition to the disubstituted product, these transformations afford substantial amounts of isomeric 4- and 5-ferrocenyl-2-methylpyridazin-3(2H)-ones, and a unique asymmetric bi-pyridazinone-bridged ferrocenophane with a screwed molecular architecture. The reactions of phenylboronic acid, conducted under the conditions, are proven to be the most reductive in the conversions of ferroceneboronic acid, and produce 2-methyl-4,5-diphenylpyridazin-3(2H)-one as single product, supporting our view about solvent-mediated hydrodehalogenations that are supposed to proceed via the assistance of the ferrocenyl group present in the reaction mixture, or attached to the bromo-pyridazinone scaffold, which is constructed in the first SM coupling of the heterocyclic precursor. A comparative DFT modelling study on the structures and possible transformations of relevant bromo-, ferrocene- and phenyl-containing carbopalladated intermediate pairs was carried out, providing reasonable mechanisms suitable to account for the apparently surprising regioselectivity of the alternative hydrodebromination processes, and for the formation of the ferrocenophane product. Supporting the results of DFT modelling studies, the implication of DMF as a hydrogen transfer agent in the hydrodebromination reactions is evidenced by deuterium labelling experiments using the solvent mixtures DMF-d7–H2O (4:1) and DMF–D2O (4:1). The organometallic products display antiproliferative effects on human malignant cell lines.

Synthetic well log modeling with light gradient boosting machine for Assam-Arakan Basin, India

Synthetic logs can help in the identification of petrophysical and geological properties of reservoirs, where the actual well logs are incomplete or absent. This study presents new and novel machine learning (ML) algorithms to generate pseudo well logs using the readily available conventional wireline logs. The machine learning algorithm works well with conventional wireline logs because they can deduce implicit relationships and efficiently detect trends in the logs. Moreover, identifying ups and downs (or peaks and valleys) of the subsurface characteristics is essential for any log. In this work, we have elucidated the application of Light Gradient Boosting Machine (LightGBM) and compared its performance with Category Boosting (CatBoost) and Random Forest (RForest). Grid search cross-validation (GridSearchCV) was done to optimize the hyperparameters of the algorithms towards a better balancing between accuracy and speed. To check the robustness of the algorithms, a number of input and output logs, considering variation in trends of logs with depth, were chosen to train the network. The well logs from Assam-Arakan Basin (India) include neutron porosity (NPHI) log, photoelectric (PE) log, caliper (CALI) log, density correction (DRHO) log, gamma-ray (GR) log, and bulk density (RHOB) log along with depth. We have evaluated the well log models and machine learning algorithms using determination coefficient (R2), mean square error (MSE), and root mean square error (RMSE) for training, testing, and validation. It has been shown that the use of machine-learning algorithms to generate synthetic logs improves reservoir characterization since they are computationally efficient, accurate, and cost-effective. The results showed that the LightGBM outperformed all the other algorithms in terms of speed and accuracy, in addition to its simplified hyperparameter tuning.