bluuebunny/crossref_metadata_2025_split huggingface dataset:
Qualification Method for Cut Resistant Jackets for Fiber Mooring Ropes
Authors: Gabrielsen Øystein , Larsen Kjell , Gjøsund Svein Helge , Reite Karl-Johan , Eide Kurt , Haugland Hans-Jørgen , Leao Alberto 
Published: August 2021

Abstract
The Aasta Hansteen spar platform in the Norwegian Sea has a polyester rope mooring system. The anchors and large parts of the polyester ropes are outside of the safety exclusion zone granted by the Norwegian authorities. Fishing vessels cannot be denied as long as they are outside of the safety zone, and the polyester mooring ropes need to withstand abrasion loads from the possible fishing activity. A fishing activity study in 2013 defined probability for fishing, size of possible fishing vessels and type of fishing equipment. Numerical simulations of the mooring system and crossing fishing trawl equipment made it possible to establish trawl abrasion load cases, including trawl wire lengths, speed and contact pressure.
No jacket design or jacket material was at the time confirmed to withstand the established abrasion loads. The jacket solution to be chosen for the project thus needed to be specially developed, designed, tested and approved to give sufficient resistance against the established abrasion loads. Several vendors developed and offered different jacket solutions, and the selection of cut resistant jacket was dependent on adequate testing. Based on input and comments from Equinor and rope vendors, DNV constructed a test rig extension to their 2500T horizontal test bed, where the required length of trawl wire was pulled over the polyester rope with the needed contact pressure. Full-size (diameter) ropes with the proposed cut resistant jackets were tested, including break strength testing after the abrasion test.
This paper presents how the possible trawl activity was defined, the numerical simulation of trawl/mooring line interaction, the test rig setup and some test results of the trawl wire abrasion testing.
Hybrid Modeling In Unconventional Reservoirs To Forecast Estimated Ultimate Recovery
Authors: Temizel Cenk , Canbaz Celal Hakan , Balaji Karthik , Ozesen Ahsen , Yanidis Kirill , Alsaheib Hasanain , AlSulaiman Nouf , Basri Mustafa , Jama Nayif 
Published: August 2021

Abstract
Machine learning models have worked as a robust tool in forecasting and optimization processes for wells in conventional, data-rich reservoirs. In unconventional reservoirs however, given the large ranges of uncertainty, purely data-driven, machine learning models have not yet proven to be repeatable and scalable. In such cases, integrating physics-based reservoir simulation methods along with machine learning techniques can be used as a solution to alleviate these limitations. The objective of this study is to provide an overview along with examples of implementing this integrated approach for the purpose of forecasting Estimated Ultimate Recovery (EUR) in shale reservoirs.
This study is solely based on synthetic data. To generate data for one section of a reservoir, a full-physics reservoir simulator has been used. Simulated data from this section is used to train a machine learning model, which provides EUR as the output. Production from another section of the field with a different range of reservoir properties is then forecasted using a physics-based model. Using the earlier trained model, production forecasting for this section of the reservoir is then carried out to illustrate the integrated approach to EUR forecasting for a section of the reservoir that is not data rich.
The integrated approach, or hybrid modeling, production forecasting for different sections of the reservoir that were data-starved, are illustrated. Using the physics-based model, the uncertainty in EUR predictions made by the machine learning model has been reduced and a more accurate forecasting has been attained. This method is primarily applicable in reservoirs, such as unconventionals, where one section of the field that has been developed has a substantial amount of data, whereas, the other section of the field will be data starved. The hybrid model was consistently able to forecast EUR at an acceptable level of accuracy, thereby, highlighting the benefits of this type of an integrated approach.
This study advances the application of repeatable and scalable hybrid models in unconventional reservoirs and highlights its benefits as compared to using either physics-based or machine-learning based models separately.
Seismic Coefficients for Simplified Deepwater Slope Stability Assessment Under Earthquake Loading
Authors: Trandafir Aurelian C. 
Published: August 2021

Abstract
Pseudostatic limit-equilibrium based slope stability analyses are carried out on a routine basis to evaluate stability of submarine slopes under earthquake loading. For slopes in deepwater settings, a major challenge in performing pseudostatic slope stability analyses is selection of an appropriate seismic coefficient. Most published displacement-based methodologies for seismic coefficient selection were developed using simplified sliding block models for seismic slope performance evaluation that are unable to capture the complex deformation mechanism of deepwater slopes during earthquakes. To address this challenge, this study employs two-dimensional dynamic finite-element based deformation analysis to investigate the earthquake response of submarine clay slopes characterized by morphology, stratigraphic architecture and geotechnical properties representative for the deepwater environment. Finite-element computed seismic slope performance indicators, including horizontal peak ground acceleration at the seafloor and earthquake-induced maximum shear strain within the slope, along with horizontal seismic coefficients required to trigger slope instability in limit-equilibrium based pseudostatic stability analyses are used to develop a rational shear strain-based correlation relationship for deepwater slope seismic coefficient selection.
Pore–Scale Study of Effects of Hydrate Morphologies on Dissociation Evolutions Using Lattice–Boltzmann Method
Authors: Li Zhuoran , Qin Guan 
Published: August 2021

AbstractThe natural gas hydrate, plentifully distributed in ocean floor sediments and permafrost regions, is considered a promising unconventional energy resource. The investigation of hydrate dissociation mechanisms in porous media is essential to optimize current production methods. To provide a microscopic insight in the hydrate dissociation process, we developed a Lattice Boltzmann (LB) model to investigate this multi–physicochemical process, including mass transfer, conjugate heat transfer, and gas transport. The methane hydrate dissociation is regarded as the reactive transport process coupled with heat transfer. The methane transport in porous media is modelled by the generalized LB method with the Bhatnagar-Gross-Krook (BGK) collision model. The mass transfer from hydrate to fluid phase is described by the hydrate kinetic and thermodynamic models. Finally, the conjugate heat transfer LB-model for heterogeneous media is added for solving the energy equation.In the numerical experiments, we primarily investigated the effects of different hydrate distribution morphologies such as pore–filling, grain–coating, and dispersed on the hydrate dissociation process. From simulations, we found that in general, the dissociation rate and the methane average density rapidly approached the maximum value and then decreased with fluctuation during the dissociation process. This trend is due to that the endothermic reaction heat decreased the temperature, resulting in decelerating the dissociation. The average temperature decreased to minimum value instantaneously as hydrate started to dissociate. After the minimum value, the average temperature would increase slowly, accompanied by the thermal stimulation and hydrate consumption, displaying a valley shape of the temperature curve. We also found that the whole dissociation process and permeability–saturation relations are significantly affected by the hydrate morphologies. Under the same hydrate saturation, the dispersed case dissolves the fastest, whereas the grain–coating case is the slowest. Furthermore, we proposed a general permeability–saturation relation applicable for three cases, filling the gap in the current relative permeability models. The LB model proposed in this study is capable to simulate the complex physicochemical hydrate dissociation process. Considering the impacts of thermodynamic conditions (P,T), we investigated their influences on the coupled interaction between dissociation and seepage under three different morphologies and proposed a general permeability–saturation relationship. The results can be applied as input to adjust parameters in the continuum model, and provide instructions for exploring clean energy with environmental considerations.
Modeling Production Facilities Using Conventional Process Simulators and Data Validation and Reconciliation DVR Methodology
Authors: Mooney Tom , Bratley Kelda , Amin Amin , Jadot Timothy 
Published: August 2021

Abstract
The use of conventional process simulators is commonplace for system design and is growing in use for online monitoring and optimization applications. While these simulators are extremely useful, additional value can be extracted by combining simulator predictions with field inputs from measurement devices such as flowmeters, pressure and temperature sensors. The statistical nature of inputs (e.g., measurement uncertainty) are typically not considered in the forward calculations performed by the simulators and so may lead to erroneous results if the actual raw measurement is in error or biased.
A complementary modeling methodology is proposed to identify and correct measurement and process errors as an integral part of a robust simulation practice. The studied approach ensures best quality data for direct use in the process models and simulators for operations and process surveillance. From a design perspective, this approach also makes it possible to evaluate the impact of uncertainty of measured and unmeasured variables on CAPEX spend and optimize instrument / meter design.
In this work, an extended statistical approach to process simulation is examined using Data Validation and Reconciliation, (DVR). The DVR methodology is compared to conventional non-statistical, deterministic process simulators. A key difference is that DVR uses any measured variable (inlet, outlet, or in between measurements), including its uncertainty, in the modelled process as an input, where only inlet measurement values are used by traditional simulators to estimate the values of all other measured and unmeasured variables.
A walk through the DVR calculations and applications is done using several comparative case studies of a typical surface process facility. Examples are the simulation of commingled multistage oil and gas separation process, the validation of separators flowmeters and fluids samples, and the quantification of unmeasured variables along with their uncertainties. The studies demonstrate the added value from using redundancy from all available measurements in a process model based on the DVR method.
Single points and data streaming field cases highlight the dependency and complementing roles of traditional simulators, and data validation provided by the DVR methodology; it is shown how robust measurement management strategies can be developed based on DVR’s effective surveillance capabilities. Moreover, the cases demonstrate how DVR-based capex and opex improvements are derived from effective hardware selection using cost versus measurement precision trade-offs, soft measurements substitutes, and from condition-based maintenance strategies.
A New Insight into Hybrid Surfactant and Low Salinity/Engineered Water Injections in Carbonates Through Geochemical Modeling
Authors: Adila Ahmed S. , Al-Shalabi Emad W. , Alameri Waleed 
Published: August 2021

Abstract
Low salinity/engineered water injections (LSWI/EWI) have gained popularity as effective techniques for enhancing oil recovery. Surfactant flooding is also a well-established and commercially-available technique in the oil and gas industry. In this paper, a numerical 2D simulation model was developed to investigate the effect of hybrid surfactant-LSWI/EWI on oil recovery from carbonate cores under harsh conditions. The developed simulation model was validated by history-matching recently conducted surfactant corefloods in the secondary mode of injection. Oil recovery, pressure drop, and surfactant concentration data were utilized. The surfactant flooding model was then coupled with a geochemical model that captures different reactions during LSWI/EWI. The geochemical reactions considered include aqueous, dissolution/precipitation, and ion-exchange reactions. Different simulation scenarios were considered and compared including waterflooding, surfactant flooding, engineered water injection, hybrid surfactant-EWI, and hybrid surfactant-LSWI. Additionally, sensitivity analysis was performed on the hybrid surfactant-EWI process through capturing changes in surfactant injected concentration and adsorption.
For the case of LSWI/EWI, wettability alteration was considered as the main mechanism underlying incremental oil recovery. However, both wettability alteration and interfacial tension reduction mechanisms were considered for surfactant flooding depending on the type of surfactant used. The results showed that the hybrid surfactant-EWI altered the wettability and achieved higher oil recovery than that of surfactant-LSWI and other techniques. This highlights the importance of selecting the right combinations of potential ions for a certain reservoir to maximize oil recovery rather than a simple water dilution. The results also highlight the importance of surfactant adsorption and surfactant concentration for the hybrid surfactant-EWI technique. This work provides insights into the application of hybrid surfactant-LSWI/EWI on oil recovery especially in carbonates. The novelty of this work is further expanded through comparing surfactant-LSWI with surfactant-EWI and understanding the controlling parameters of surfactant-EWI through sensitivity analysis.
Critical Review of the Thai and Malaysian Decommissioning Landscapes
Authors: Tung Aaron , Wanarunwong Wanarun , Vuttipittayamongkol Pattaramon 
Published: August 2021

Abstract
As the wave of oil and gas decommissioning activities begins across Thailand and Malaysia, issues related to the management of oil and gas decommissioning activities also begin to take shape, appearing in the form of disputes (Tanakasempipat 2019), schedule delays (Zainal Abidin and Mahasan 2019), scope creeps (Xu et al. 2019; Yap 2018), and cost overruns (Yusof, Ros and Omar 2018). One avenue to overcome the issues related to the management of oil and gas decommissioning activities in Thailand and Malaysia, is to enhance project managers’ understanding of the Thai and Malaysian oil and gas decommissioning landscape. Therefore, a research involving semi-structured interviews with 20 industrial representatives was conducted over the period of 2019 and 2020.
This paper presents the findings from the research, detailing the regulatory structure and process, the supply chain and research capabilities, the operator's planning and execution behaviours for oil and gas decommissioning, and public stakeholders’ behaviours towards oil and gas decommissioning activities. The research findings will be presented in the form of a list of considerations, which project managers can utilize when managing future oil and gas decommissioning activities in Thailand and Malaysia. In addition, emergent research findings will also be summarized as a list recommendations for legislative and regulatory government bodies in order to further enhance the effectiveness of current regulatory arrangements.
MACRO-GOM: Long Term Multi-Resolution Ocean Current Reanalysis Dataset for the Gulf of Mexico
Authors: Groves Neha , Srinivasan Ashwanth , Ivanov Leonid , Storie Jill , Gustafson Drew , Ramos Rafael 
Published: August 2021

Abstract
The Gulf of Mexico's unique circulation characteristics pose a particular threat to marine operations and play a significant role in driving the criteria used for design and life extension analyses of offshore infrastructure. Estimates from existing reanalysis datasets used by operators in GOM show less than ideal correlation with in situ measurements and have a limited resolution that disallows for the capture of ocean features of interest. In this paper, we introduce a new high-resolution long-term reanalysis dataset, Multi-resolution Advanced Current Reanalysis for the Ocean – Gulf of Mexico (MACRO-GOM), based on a state-of the-science hydrodynamic model configured specifically for ocean current forecasting and hindcasting services for the offshore industry that assimilates extensive non-conventional observational data. The underlying hydrodynamic model used is the Woods Hole Group – Tendral Ocean Prediction System (WHG-TOPS). MACRO-GOM is being developed at the native resolution of the TOPS-GOM domain, i.e. 1/32° (~3 km) hourly grid for the 1994-2019 time period (25 years). A 3-level downscaling methodology is used wherein observation based estimates are first dynamically interpolated using a 1/4° model before being downscaled to the 1/16° Inter-American Seas (IAS) domain, which in turn is used to generate time-consistent boundary conditions for the 1/32° reanalysis. A multiscale data assimilation technique is used to constrain the model at synoptic and longer time scales. For this paper, a shorter, 5-year reanalysis run was conducted for the 2015-2019 time period for verification against assimilated and unassimilated observations, WHG's proprietary frontal analyses, and other reanalyses. Both the frontal analyses and Notice to Lesses (NTL) rig mounted ADCP data was withheld from assimilation for comparison. Offshore operations in the GOM can benefit from an improved reanalysis dataset capable of assimilating existing non-conventional observational datasets. Existing hindcast and reanalysis model datasets are limited in their ability to comprehensively and reliably quantify the 3D circulation and kinematic properties of the main features partly because of limited assimilation of observational data. MACRO-GOM incorporates all the advantages of available HYCOM-based reanalyses and further enhances the resolution, accuracy, and reliability by the assimilation of over three decades of WHG's proprietary datasets and frontal analyses for continuous model correction and ground-truthing. The final 25-year high resolution dataset will provide highly reliable design and operational criteria for new and existing infrastructure in GOM.
Reducing THI Injection and Gas Hydrate Agglomeration by Under-Inhibition of Crude Oil Systems
Authors: Delgado-Linares Jose G. , Majid Ahmad A.A. , Zerpa Luis E. , Koh Carolyn A. 
Published: August 2021

Abstract
Gas hydrates constitute a serious flow assurance problem. Over the last decades, industry has faced this problem by using avoidance methods (e.g. injection of thermodynamic hydrate inhibitors) and management strategies (e.g. addition of hydrate anti-agglomerants). In the former, hydrates are completely avoided by shifting the hydrate boundary towards higher pressure and lower temperatures; in the latter, hydrates are allowed to form but their tendency to agglomerate is reduced. It should be noted that some crude oils are naturally able to avoid hydrate agglomeration, this non-plugging tendency may originate from the surfactant-like behavior of fractions like asphaltenes and acids. Recent works have shown that the natural non-plugging potential of certain oils can be affected by the addition of polar molecules like alcohols.
There is another strategy for managing hydrate that consist of the addition of THIs at a concentration lower that the one required to full hydrate inhibition. In this case, hydrates are under-inhibited. Studies carried out on hydrate agglomerating systems have shown that under-inhibition might prevent hydrate agglomeration only in a specific range of THI concentrations and sub-cooling; however, work on non-plugging oils is scarce. In this paper, the hydrate agglomeration of two crude oils under-inhibited with methanol and MEG was evaluated through a visual rocking cell apparatus and a high-pressure rheometer. Results showed that THIs and the crude oil's natural surfactants were capable of acting synergistically in reducing hydrate agglomeration and improving the system flowability.
New Insights into Geochemical Modeling of Hybrid Low Salinity/Engineered Water and Polymer Injections in Carbonates
Authors: Al-Shalabi Emad W. , Alameri Waleed 
Published: August 2021

Abstract
For decades, polymer flooding proved to be one of the most effective enhanced oil recovery (EOR) methods. In addition, low salinity/engineered water injection (LSWI/EWI) has been gaining momentum over the last few years. Both techniques seem to be cheaper than other EOR methods. This resulted in an increased interest among operators in these techniques. Moreover, low-salinity water is usually less viscous compared to formation fluids, which warrants a lower volumetric sweep efficiency, especially at high temperatures and in highly heterogeneous formations. The reduction in macroscopic sweep efficiency impairs the improvement in recovery efficiency by low-salinity water. In addition, experimental studies showed that polymer viscosity is considerably improved in less saline water. In this study, hybrid polymer and LSWI/EWI flooding performance is numerically evaluated in carbonate formations under conditions of mixed-to-oil wettability, high temperature, high salinity, and low permeability.
A numerical 1D model was constructed using a commercial compositional simulator. The model captures the polymer rheology of a newly developed and commercially available synthetic polymer. Also, the effect of LSWI/EWI on polymer rheology and performance was studied. Oil recovery, pressure drop, and in-situ saturation data were history matched for seawater, polymer, and low salinity water injection cycles. Furthermore, the matched experimental data were utilized to examine the combined polymer and low salinity water effect on the improvement in microscopic displacement efficiency of linear models under reservoir flow conditions. The simulation results showed that hybrid polymer and LSWI/EWI is a viable EOR method for carbonate reservoirs under harsh conditions. Moreover, this work provides new insights into the hybrid application of LSWI/EWI and polymer flooding in carbonates under harsh conditions, the impact of low-salinity water on in-situ polymer rheology, and it promotes further field-scale applications of hybrid polymer-LSWI/EWI to improve volumetric sweep efficiency and overall recovery efficiency.