Instantaneous Model Research Articles

A Global-Scale Overlapping Pixels Calculation Method for Whisk-Broom Payloads with Multi-Module-Staggered Longlinear-Array Detectors

A multi-module staggered (MMS) long-linear-array (LLA) detector is presently recognized as an effective and widely adopted means of improving the field of view (FOV) of in-orbit optical line-array cameras. In particular, in terms of low-orbit whisk-broom payloads, the MMS LLA detector combined with the one-dimensional scanning mirror is capable of achieving both large-swath and high-resolution imaging. However, because of the complexity of the instantaneous relative motion model (IRMM) of the whisk-broom imaging mechanism, it is really difficult to determine and verify the actual numbers of overlapping pixels of adjacent detector sub-module images and consecutive images in the same and opposite scanning directions, which are exceedingly crucial to the instrument design pre-launch as well as the in-orbit geometric quantitative processing and application post-launch. Therefore, in this paper, aiming at addressing the problems above, we propose a global-scale overlapping pixels calculation method based on the IRMM and rigorous geometric positioning model (RGPM) of the whisk-broom payloads with an MMS LLA detector. First, in accordance with the imaging theory and the specific optical–mechanical structure, the RGPM of the whisk-broom payload is constructed and introduced elaborately. Then, we qualitatively analyze the variation tendency of the overlapping pixels of adjacent detector sub-module images with the IRMM of the imaging targets, and establish the associated overlapping pixels calculation model based on the RGPM. And subsequently, the global-scale overlapping pixels calculation models for consecutive images of the same and opposite scanning directions of the whisk-broom payload are also built. Finally, the corresponding verification method is presented in detail. The proposed method is validated using both simulation data and in-orbit payload data from the Thermal Infrared Spectrometer (TIS) of the Sustainable Development Goals Satellite-1 (SDGSAT-1), launched on 5 November 2021, demonstrating its effectiveness and accuracy with overlapping pixel errors of less than 0.3 pixels between sub-modules and less than 0.5 pixels between consecutive scanning images. Generally, this method is suitable and versatile for the other scanning cameras with a MMS LLA detector because of the similarity of the imaging mechanism.

Internal Tides From SWOT: A 75‐Day Instantaneous Mode‐1 M2 ${\mathrm{M}}_{2}$ Internal Tide Model

AbstractSeventy‐five days of sea surface height measurements made by the Surface Water and Ocean Topography (SWOT) mission from 7 September to 21 November 2023 are used to explore SWOT's capability of observing internal tides. Mode‐1 internal tides are mapped by our updated mapping technique. SWOT‐75d represents a 75‐day instantaneous model. Nadir‐30y is constructed using 30 years of nadir altimetry data from 1993 to 2022 and represents a climate normal. The nadir altimetry data in 2023 are used for model evaluation. Despite its large errors, SWOT‐75d reveals the basic features of the global mode‐1 internal tide field, and causes positive variance reduction in regions of strong internal tides. Nadir‐30y performs better overall, but SWOT‐75d performs better in the tropical South Atlantic Ocean, the central North Pacific Ocean, and the Melanesian region. Evaluation using seasonally subsetted altimetry data reveals that internal tides have significant temporal variations. SWOT‐75d performs the best in fall, because the model is constructed using data largely in fall. SWOT‐75d has large phase anomalies, which are spatially smoothed and used to adjust the phases in Nadir‐30y. The phase‐adjusted model can better make internal tide correction for SWOT and its performance is improved by 20%. Our results demonstrate that (a) mode‐1 internal tides can be extracted from 75 days of SWOT data by our mapping technique, and (b) the instantaneous internal tide model can be used to improve internal tide correction for SWOT.

Retention of T-bar anchor tags by adult steelhead during their upstream migration

Abstract Objective T-bar anchor tags can be used to obtain recapture data from anglers, directly estimate exploitation, and evaluate population dynamics. However, their use by biologists to study anadromous salmonid fisheries is limited. Two hurdles to adoption include the functional difficulty of tagging large anadromous salmonids using conventional tagging equipment and a lack of information on tag loss by large anadromous salmonids and how it changes over time. As such, our objectives were to (1) describe a T-bar anchor tagging system modified to study adult steelhead Oncorhynchus mykiss (anadromous Rainbow Trout) and (2) present an instantaneous tag loss model for steelhead that allows estimation of tag loss over time. Methods First, we developed a modified tagging system by tagging hatchery-obtained steelhead carcasses and live, resident Rainbow Trout larger than 500 mm using a variety of hardware and tag dimensions. Next, we double-tagged adult steelhead captured at the Lower Granite Dam adult fish trap, Washington, United States. We then used data from 182 recaptured steelhead to fit an instantaneous tag loss model. Last, we investigated whether steelhead tag loss was related to body length. Result Tag loss was generally low within the time period under study (i.e., up to 221 days between release and recapture). The estimated probability of tag loss was 0.034 at release, 0.044 at 1 month, and 0.113 at 8 months. We failed to detect significant differences in tag loss parameters between two data subsets consisting of small (<720-mm) and large (≥720-mm) steelhead. Conclusion T-bar anchor tags are useful external tags for studying adult steelhead during their upstream migration. Because anglers can be used to provide recapture data, T-bar anchor tags may be particularly useful where angler effort is high or direct estimation of fishery exploitation is desired.

Most AOTL type A and type B thoracolumbar primary fracture line follow the mechanism of an imaging-based injury model.

Based on the phenomenon that most thoracolumbar primary fracture line passes the center of the pedicle, we proposed an injury mechanism model to evaluate. Consecutive patients with thoracolumbar fractures treated operatively between October 2019, and December 2020 were analyzed retrospectively. Demographic and spinal radiographical parameters were measured and recorded. Pedicle hyperintensity on T2-weighted sagittal MR images was labeled. We examined the relationship between the course of the line (Radius) connecting the center of the pedicle of the injured vertebra and the IAR and orientation of the thoracolumbar primary fracture line. A partial correlation test was calculated to find correlations between demographic and spinal radiographical parameters. Nonlinear regression analysis was run with the Radius as the dependent variable and the other spinal kyphosis parameters as the independent variables to verify this model. Ninety-seven patients with 104 thoracolumbar fractures were included in this study. Ninety-four (90.4%) thoracolumbar fractures showed a high signal on MRI T2 through the pedicle. Involvement of the center of the pedicle was distributed among most AOTL Type A and Type B thoracolumbar fractures. In total, 92.3% of primary vertebral fracture lines followed the Radius of the model (r2 = 0.940). We provide a simple and quantifiable spinal instantaneous injury mechanism model for thoracolumbar fractures. Specifically, most AOTL type A and B thoracolumbar primary fracture line conforms to this model.

An improved instantaneous gross primary productivity model considering the difference in contributions of sunlit and shaded leaves to canopy sun-induced chlorophyll fluorescence

Sun-induced chlorophyll fluorescence (SIF) from plants offers an effective proxy for estimating gross primary productivity (GPP) by modeling SIF-GPP relationships, a widely used method to evaluate the global carbon sink. However, most SIF-GPP models ignore SIF differences between shaded and sunlit leaves, resulting in GPP underestimation, particularly in dense vegetation. This study aims to partition the contributions of sunlit and shaded leaves to canopy SIF and GPP to refine the SIF-GPP estimation model. Data from 40 eddy covariance (EC) sites representing eight major biomes and TROPOMI SIF satellite data were used for site-specific and global-scale analyses. Our results showed that the contributions of sunlit and shaded leaves to canopy SIF were 80 % and 20 %, and to canopy GPP were 55 % and 45 %, respectively. For site-specific or satellite data, the SIF-GPP relationships were the strongest for sunlit leaves (R2 > 0.51, RMSE = 4.03 μmol m−2 s−1, p < 0.001). The new SIF-GPP model, including sunlit-shaded SIF separation, can improve the accuracy of GPP estimation (R2 = 0.53, RMSE = 4.38 μmol m−2 s−1, p < 0.001). Compared with the model established with observed data, R2 was increased by 0.1, and RMSE decreased by 13.26 μmol m−2 s−1, indicating that the ‘two-leaf’ model could notably improve the SIF-GPP model. This study confirms the different contributions of sunlit and shaded leaves to canopy SIF and GPP, and ignoring this disparity would induce systematic bias in GPP estimation. Our methods and findings on sunlit-shaded SIF separation can be referenced by other studies to enhance GPP estimation accuracy.

Development of a source-term migration model for a large bubble formed in a core disruptive accident

Because sodium-cooled fast reactors are designed with high inherent safety in mind, the probability of a core disruptive accident (CDA) is extremely low. However, from a defense-in-depth perspective, the study of CDA sequences is still worthwhile to assure the safety and reliability of reactors. During a CDA, a large bubble rapidly expands inside the sodium pool, rises from the core, and covers the gas region, providing a potential migration path for source terms (radioactive materials present within the containment barriers). Source terms released initially within the cover-gas region after a few hundred milliseconds are called instantaneous source terms. We propose here an instantaneous source-term migration model that provides a simplified evaluation of the amount of source terms absorbed by coolant sodium during the ascent of the CDA bubble. In the model, the particle motion within the CDA bubble obtained from the basic momentum equation is used to calculate the amount of source terms escaping from the bubble interface. In addition, a model analogous to aerosol scavenging by precipitation is used to assess the amount of source terms absorbed by droplets present in the bubble, especially the entrained sodium droplets that form during rapid expansion of the CDA bubble. The model is further validated by a previous source term migration experiment in which a large high-pressure bubble expands and rises in a sodium pool. Good agreement with the measured retention factor of a source term demonstrates the reliability of the developed model. Given these results, some key parameters are selected for a sensitivity analysis.

Visualized generator for the simulation of wastewater quality and quantity variations in the sewer system

Data generators are imperative to support design, management, scenario simulation, risk assessment, and regulatory compliance. Hybrid sewer systems struggle with accurate water quality and quantity monitoring due to variable flow patterns, missing connections, limited monitoring capacity. To accurately regenerate operational data for hybrid sewer system along the sewer shed, a visualized generator was developed to simulate wastewater quantity and quality variations within different scales in the sewer system. The generator was constructed using a multi-level, tree-structured model incorporating various modules, including domestic, industrial, WWTP, and pump stations, to simulate time series variations. A novel instantaneous unit pollutant-hydrograph modeling associated with wastewater conductivity monitoring data was proposed in the generator. The validated generation data of flow, COD, ammonia nitrogen, and phosphate were well-fitted with the full-scale measured data in residential areas, pump stations, and WWTPs. The proposed generator could be used to predict and simulate the dynamic flow and wastewater quality variations at different scale regions in sewer network-wide to support the operation and management of pump stations and WWTPs. The generator modules enable accurate simulation and visualization of water quality and quantity in hybrid sewer system, enhancing the understanding of infiltration, inflow, and pollutant dynamics, especially under challenging conditions like simultaneous RDII and overflow.

Advancing instantaneous detonation prediction of condensed energetic materials based on high-order compressible multiphase fluid dynamics

The instantaneous detonation model (IDM) is widely used in simulating underwater explosions due to its efficiency and ability to ignore the detonation reaction process. In this study, we propose a new IDM to predict the fluid structure in the detonation zone of an RS211 explosive charge. This model is based on high-order solutions provided by the detonation shock dynamics model, where the spatial term is discretized using fifth-order WENO reconstruction in characteristic space and Lax–Friedrichs’s splitting and the temporal terms are discretized using a third-order TVD Runge–Kutta scheme. The interface motion is captured using the level-set method combined with MGFM, and a programmed burn model is provided to describe the generation and propagation of the detonation wave. The self-similarity of detonation wave propagation is validated, and the quantitative calculation formula of the instantaneous detonation model is obtained by averaging or curve fitting the dimensionless results. Consequently, the IDM of the RS211 charge is established using high-order polynomial approximations of the Taylor rarefaction zone and a constant static zone for 1D planar, cylindrical, and spherical RS211 charges. The application of the IDM involves direct mapping from the radial direction to the spatial structured grid for 1D planar, 2D cylindrical, and 3D spherical charges. Numerical results demonstrate that the IDM proposed in this paper shows good accuracy and high computational efficiency.

Potential of Soft-Shelled Rugby Headgear to Lower Regional Brain Strain Metrics During Standard Drop Tests

BackgroundThe growing concern for player safety in rugby has led to an increased focus on head impacts. Previous laboratory studies have shown that rugby headgear significantly reduces peak linear and rotational accelerations compared to no headgear. However, these metrics may have limited relevance in assessing the effectiveness of headgear in preventing strain-based brain injuries like concussions. This study used an instantaneous deep-learning brain injury model to quantify regional brain strain mitigation of rugby headgear during drop tests. Tests were conducted on flat and angled impact surfaces across different heights, using a Hybrid III headform and neck.ResultsHeadgear presence generally reduced the peak rotational velocities, with some headgear outperforming others. However, the effect on peak regional brain strains was less consistent. Of the 5 headgear tested, only the newer models that use open cell foams at densities above 45 kg/m3 consistently reduced the peak strain in the cerebrum, corpus callosum, and brainstem. The 3 conventional headgear that use closed cell foams at or below 45 kg/m3 showed no consistent reduction in the peak strain in the cerebrum, corpus callosum, and brainstem.ConclusionsThe presence of rugby headgear may be able to reduce the severity of head impact exposure during rugby. However, to understand how these findings relate to brain strain mitigation in the field, further investigation into the relationship between the impact conditions in this study and those encountered during actual gameplay is necessary.

A model for operational risk of industrial facilities including ageing/test degradation effects and maintenance effectiveness

The paper presents a model for operational risk of industrial facilities with applications to nuclear power plants and uranium mining. The traditional models update the risk profile for specific operational conditions setting to one the failure probability of components which are known to be unavailable by failure or maintenance, while constant mean unavailability values from the original Probabilistic Safety Analysis (PSA) are kept for the rest. The proposed methodology considers the time dependency of standby failure probabilities through instantaneous unavailability models, depending on the specific standby time for each component at the given moment, instead of using the same constant values. It also incorporates ageing, testing degradation effects and maintenance effectiveness, not explicitly considered in traditional models, as well as the instantaneous reevaluation of common cause failure probabilities. The results show significant risk underestimations when components specific standby times, ageing, testing degradation effects and maintenance effectiveness are not considered.

The Role of Upper Mantle Forces in Post‐Subduction Tectonics: Plumelet and Active Rifting in the East Anatolian Plateau

AbstractThe spatiotemporal interaction of large‐ and regional‐scale upper mantle forces can prevail in collisional settings. To better understand the role of these forces on post‐subduction tectonics, we focus on mantle dynamics in the East Anatolian Plateau, a well‐documented segment of the Arabian‐Eurasian continental collision zone. Specifically, we analyze multiple forces in the upper mantle, which have not been considered in previous studies in this region. To this end, we use a state‐of‐the‐art 3D instantaneous geodynamic model to quantify the dynamics of thermally defined upper mantle structures derived from seismic tomography data. Results reveal a prominent SW‐NE‐oriented mantle flow from the Arabian foreland to the Greater Caucasus–a plumelet–through a lithospheric channel under the East Anatolian Plateau. This plumelet induces localized dynamic topography (∼500 m) around the extensional Lake Van province, favoring NE‐directed compression and westward escape of the Anatolian plate. We suggest that the Lake Van region is an active magma‐rich intraplate rift in the Africa‐Arabia‐Anatolian plume‐rift system. The rift zone was probably initiated by Neotethyan subduction‐related forces and has been reactivated and/or sustained by the plumelet‐induced convective support. Our findings are consistent with numerous observations, including the recent low‐ultralow seismic velocities with a SW‐NE splitting anisotropy pattern, geochemical and petrological studies, and local kinematics showing upper mantle‐induced extensional tectonics in the collisional region.

Delayed kernels for longitudinal survival analysis and dynamic prediction.

Predicting patient survival probabilities based on observed covariates is an important assessment in clinical practice. These patient-specific covariates are often measured over multiple follow-up appointments. It is then of interest to predict survival based on the history of these longitudinal measurements, and to update predictions as more observations become available. The standard approaches to these so-called 'dynamic prediction' assessments are joint models and landmark analysis. Joint models involve high-dimensional parameterizations, and their computational complexity often prohibits including multiple longitudinal covariates. Landmark analysis is simpler, but discards a proportion of the available data at each 'landmark time'. In this work, we propose a 'delayed kernel' approach to dynamic prediction that sits somewhere in between the two standard methods in terms of complexity. By conditioning hazard rates directly on the covariate measurements over the observation time frame, we define a model that takes into account the full history of covariate measurements but is more practical and parsimonious than joint modelling. Time-dependent association kernels describe the impact of covariate changes at earlier times on the patient's hazard rate at later times. Under the constraints that our model (a) reduces to the standard Cox model for time-independent covariates, and (b) contains the instantaneous Cox model as a special case, we derive two natural kernel parameterizations. Upon application to three clinical data sets, we find that the predictive accuracy of the delayed kernel approach is comparable to that of the two existing standard methods.

Advances in terminal management: simulation of vehicle traffic in container terminals

AbstractControlling and managing traffic flows on internal roads in container terminals are crucial in achieving expected productivity levels and reducing negative externalities caused by congestion inside and outside the terminal areas. This paper proposes a simulation approach which terminal operators can use as a decision-support tool to assess the effects of their management strategies and improve terminal performance, resilience, and sustainability. A microscopic traffic simulation approach models key operations of a typical container terminal affecting road traffic flows. In particular, to estimate quantitative indicators, an import truck process is reproduced, considering the overlapping of the external truck and internal trailer flows. To measure environmental impacts, the model is extended with an instantaneous emissions model linked directly to the step-by-step traffic data. The proposed method is tested on a sector of the PSA Genova Pra’, the main Italian container gateway terminal. Performance indicators related to the terminal’s efficiency and sustainability are estimated, to compare alternative scenarios considering possible operational configurations and disturbance events, such as the closure of a part of the yard. By focusing on the interactions between vehicle flows and terminal equipment operations, this approach offers a new perspective on terminal operations, oriented both towards container terminal operators and stakeholders, such as road hauliers.

Highly 002-Oriented Dendrite-Free Anode Achieved by Enhanced Interfacial Electrostatic Adsorption for Aqueous Zinc-Ion Batteries.

Rechargeable aqueous zinc-ion batteries (AZIBs) are gaining recognition as promising next-generation energy storage solution, due to their intrinsic safety and low cost. Nevertheless, the advancement of AZIBs is greatly limited by the abnormal growth of zinc dendrites during cycling. Electrolyte additives are effective at suppressing zinc dendrites, but there is currently no effective additive screening criterion. Herein, we propose employing the interfacial electrostatic adsorption strength of zinc ions for the initial screening of additives. Subsequently, dendrite-free plating is achieved by employing the anionic surfactant sodium dodecyl benzenesulfonate (SDBS) to enhance electrostatic adsorption. The cycled zinc anode exhibited a dense plating morphology and a high (002) orientation (I002/I101 = 22). The Zn||MnO2 full cell with SDBS exhibited a capacity retention of 85% after 1000 cycles at 1 A g-1. Furthermore, an instantaneous nucleation model and continuous nucleation model (CNM) are constructed to reveal the microscale plating/stripping dynamics under the scenarios of weak adsorption and strong adsorption. The CNM accurately explains the self-optimizing reconstruction of electrodes resulting from enhanced electrostatic adsorption. Our exploration was extended to other anionic surfactants (sodium dodecyl sulfate and disodium laureiminodipropionate), confirming the effectiveness of strong electrostatic adsorption in the screening of electrolyte additives.

TMPAC-EG deep eutectic solvent for sustainable recovery of Nd by electrodeposition

The electrodeposition of neodymium (Nd) in a novel analogous ionic liquid (AIL), phenyltrimethylammonium chloride-ethylene glycol (TMPAC-EG), was investigated. The existence form and the electrochemical behavior of Nd(III) in TMPAC-EG were studied using spectroscopic, cyclic voltammetry and chronoamperometry analyses. The spectroscopic analyses indicates that Nd3+ interact with Cl− and EG to form complexes [Nd(EG)6-yCly]3-y as NdCl3 dissolves in TMPAC-EG IL. Cyclic voltammograms reveals that the overpotential for Nd electrodeposition in TMPAC-EG IL decreases with the rise of the temperature. The diffusion coefficient of Nd(III) ions is calculated to about 10−12 m2 s−1. The diffusion activation energy for Nd(III) ions is determined to be 22.8 kJ mol−1 from the temperature dependence of diffusion coefficient. The transient analysis indicates that initial nucleation behavior of Nd conforms to the three-dimensional instantaneous nucleation and growth model, which are largely independent of temperature. In addition, deposition temperature and deposition potential are found to have a great influence on the nucleation and growth kinetics of Nd electrodeposition. Depending on the temperature and potential of electrodeposition, metallic neodymium with caterpillar-shape, nodule, layered rock, or porous structures was obtained.

A high precision instantaneous detonation model (hp-IDM) for condensed energetic materials and its application in underwater explosions

A high precision instantaneous detonation model (<i>hp</i>-IDM) for condensed energetic materials and its application in underwater explosions

Myocardial T1 mapping using an instantaneous signal loss simulation modeling and a Bayesian estimation method: A robust T1 extraction method free of tuning parameters

The Instantaneous Signal Loss Simulation (InSiL) model is a promising alternative to the classical mono-exponential fitting of the Modified Look-Locker Inversion-recovery (MOLLI) sequence in cardiac T1 mapping applications, which achieves better accuracy and is less sensitive to heart rate (HR) variations. Classical non-linear least squares (NLLS) estimation methods require some parameters of the model to be fixed a priori in order to give reliable T1 estimations and avoid outliers. This introduces further bias in the estimation, reducing the advantages provided by the InSiL model. In this paper, a novel Bayesian estimation method using a hierarchical model is proposed to fit the parameters of the InSiL model. The hierarchical Bayesian modeling has a shrinkage effect that works as a regularizer for the estimated values, by pulling spurious estimated values toward the group-mean, hence reducing greatly the number of outliers. Simulations, physical phantoms, and in-vivo human cardiac data have been used to show that this approach estimates accurately all the InSiL parameters, and achieve high precision estimation of the T1 compared to the classical MOLLI model and NLLS InSiL estimation.

High flow prediction model integrating physically and deep learning based approaches with quasi real-time watershed data assimilation

When operating a flood forecasting system, it is crucial to prioritize both promptness and accuracy, along with reflecting the latest watershed conditions. This study proposes a hybrid model for rainfall-induced high flow prediction that combines an instantaneous physically-based model and a deep learning-based rainfall loss model assimilating with quasi real-time watershed conditions. Its primary objective is to present immediate and reliable high flow predictions, ensuring stability in prediction procedures. The surface runoff component of the model is based on nonlinear instantaneous unit hydrograph (IUH) derived using a dynamic wave model, which considers the nonlinearity between the rainfall excess intensity and the time to peak and peak flow of the IUH. To account for rainfall loss, which can significantly influence rainfall-runoff quantity, Long Short-Term Memory (LSTM) model is employed to establish link between key rainfall loss parameters and the latest watershed conditions obtained from the Global Land Data Assimilation System (GLDAS). The application of the proposed model to 28 high flow events reveals several noteworthy outcomes. Firstly, unlike conventional models that depend on fixed parameter values specific to each event, the proposed model offers immediate, stable, and highly accurate high flow predictions without the need for manual calibration. Secondly, the prioritization of parameters reflecting watershed conditions varies between different watersheds and depends on the rainfall events. These findings indicate the necessity to estimate rainfall loss parameters individually for each rainfall-runoff event in each watershed, as no universal value exists for these parameters. Lastly, despite the limited number of test cases conducted in this study, the LSTM model achieved sufficiently accurate rainfall loss estimation for high flow prediction using only 50 datasets.

A novel approach of stability and topography prediction in five-axis ball-end milling process through workpiece-edge-coupling

By studying the workpiece-edge-coupling (WEC) in five-axis ball-end milling, the contact characteristics between the workpiece and edge curve are analyzed, and the chip model is extracted and simplified. The edge curve involved in the cutting process of each edge are calculated at each time and a new instantaneous numerical chip thickness model is established. Then the milling forces and stability lobe diagram (SLD) are calculated in following cut process with lead and tilt angle. The milling forces and SLD of lead angle at 15° and tilt angle at −15° are verified by comparing with Otzurk model as references, and it is found the SLD of WEC model can reflect the unstable points more properly than that of Otzurk model. Also the vibration in [Formula: see text] and [Formula: see text] directions show a divergence trend, which proves the high precision for the new algorithm adapted to the stability prediction of five-axis ball-end milling process. In addition, the surface topography is acquired considering lead and tilt angle as well as forced vibration, and the result is consistent with the experiment in the existing literature. It is found that the milling forces, SLD and surface topography show the same variation trend with the increase of lead and tilt angle. Besides, the stability region significantly expands and the surface topography improves by applying positive tilt angle other than the negative. Then, under the conditions of positive lead and tilt angle, increasing lead angle and decreasing tilt angle reduces the milling force, expands the stability region of SLD and improve the surface topography. The optimized tool posture is acquired by the coincident analysis of milling force, SLD and surface topography under different lead and tilt angle.

Appraisal of reservoir quality for hydrocarbon-bearing deep-water Miocene sandstones incised valley, south-east Asian offshore Indus: An application of seismic attributes and instantaneous spectral porosity quantitative reservoir simulations

Incised marine valleys (IVS) are hot topics in exploring the stratigraphic oil and gas-bearing plays. Multiple channelized sandstone lenses at varying depths [m], thicknesses [m], and porosities [%] constrain seismic impedance. The presence of hydrocarbon-bearing resources affects the seismic impedance (density (g/cc) and velocity (m/s)). Therefore, a quantitative prediction has been carried out for determining the thickness [m], porosity [%], and depths [m] of laterally distributed channelized sandstone lenses (SLS) for IVS, Indus offshore Basin (IOB), Pakistan, using 2-D instantaneous spectral porosity quantitative modelling (2DSSM), continuous wavelet transforms-based (CWT) 2-D instantaneous spectral density modelling (2DSSDM), and spectral decomposition tools. The 2DSSM remained limited in predicting the number of channelized sandstone lenses and their quantitative stratigraphic attributes. The 45-Hz-based processing of conventional 2DSSM has resolved the two channelized sandstone lenses of the stratigraphic trap. The deepest channelized sandstone lens has attained 1–6 m thickness with a lateral extent of 3 km, within the porosity range of 18–33 %. The highest confidence level for predicted petrophysical attributes such as 13 m-thick pay zones, −0.08, −0.067, and −0.07 acoustic impedances [g/c.c.*m/s], and 28 % porosities with R2 > 0.85 have validated interpretations. The response of 45-Hz CWT waveform-based inverted density and thickness simulations has predicted the highest thicknesses and lowest densities of reservoir sandstones within the meandering channel belt of the deepwater depositional system. The predicted densities and thicknesses for the coarse-grained sandstone lenses of point bars were 1.8–1.9 g/cc and 15 m, respectively. In the same way, the quantitative estimates of predicted density and simulated thickness have shown a strong coefficient correlation (R2 > 0.80), which confirms the presence of gas-bearing prospects within the IVS. The facies-controlled migration is thought to be the movement of the reservoir facies of the point bars and channelled sandstone-filled lenses to the side.