bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Reservoir Rock Typing for Supercritical CO2-Brine System in Sandstone
Authors: Akbar M. N. A. , Myhr R. 
Published: April 2024

Abstract
Dynamic reservoir rock typing is a critical yet infrequently explored aspect of CO2 storage, essential for evaluating flow characterization in dynamic reservoir modeling within aquifer reservoirs. This study introduces a new insight into the establishment of dynamic reservoir rock types for the supercritical CO2-brine system, leveraging relative permeability data and implementing it into 3D numerical reservoir simulation.
Our research draws on 22 sandstone core plugs obtained from potential CO2 storage aquifers in Alberta, Canada, encompassing measurements of relative permeabilities during primary drainage and secondary imbibition cycles. The rock typing methodology employed incorporates pore geometry and pore structure (PGS), in conjunction with the True Effective Mobility (TEM) function, to comprehensively characterize multi-phase fluid flow properties in rocks. Subsequently, we visualize the outcomes of the rock typing process through 1D and 3D model representations, including the simulation of flow characteristics through compositional numerical modeling for geological CO2 storage.
As a result, four rock groups were established based on pore geometry and pore structure relationships in the studied samples. The critical findings are that the obtained results demonstrate clear groupings of similar TEM-function curves based on relative permeabilities of both brine and CO2, observed in both drainage and imbibition experiments. Averaged relative permeability curves were derived from the TEM-function and subsequently converted them into conventional relative permeability values for each rock type. Notably, 3D numerical simulations of flow dynamics unveiled unique and contrasting multi-phase fluid behavior within each rock group, particularly evident in saturation profiles over time. Furthermore, we evaluated the correlation between residual CO2 trapping and irreducible water saturation within the rock samples. Our findings suggest an inversely proportional relationship, indicating that higher irreducible water saturation leads to lower residual CO2 trapping.
As a novelty, combining PGS rock typing and TEM-function analysis facilitated the effective and efficient grouping of capillary pressure and relative permeability data, ensuring high consistency and minimized overlap in each rock type. Moreover, this approach offers an alternative solution for averaging relative permeability data within each rock type that can greatly reduce the uncertainty of defining relative permeability input and accelerate the process of dynamic reservoir modeling.
Building Trust in AI/ML Solutions: Key Factors for Successful Adoption in Drilling Optimization and Hazard Prevention
Authors: Schaefer S. , Revheim O. 
Published: April 2024

The use of AI/ML technologies has provided breakthrough performance in automated predictive data analytics. With the increasing amount of data available during drilling operations, data driven AI/ML solutions lay out the future of current technologies for drilling optimization and hazard prevention. Fast adoption and appeal of these technologies to the industry could be explained by a few reasons: AI/ML enables digital transformation by using only real-time data without extensive requirements for contextual data so that engineering and data input processes can be fully automated;AI/ML solutions predict outputs based on the data trends allowing to solve problems where conventional models are hard to implement or are not sensitive enough to identify subtle anomalies;Targeted solutions address specific problems and become more applicable in the modern digital ecosystem,Due to previous reasons, such technologies are easier to implement and to scale up in the operational environment.
Successful adoption of AI/ML technologies lies in its validation and trust in the operational environment. Based on the project experience from various parts of the world, prerequisites for building trust have proven to be: high performance AL/ML technology;matured IT infrastructure with relevant support services to enable digital transformation;monitoring specialists in an established RTOC or rigsite team to validate solution decisions;good communication protocol and established responsibilities of the RTOC and rig team to validate the impact of the predictions and to apply for operations.
The success factors are consequently related to technology, infrastructure and "soft" aspects like work processes, team interactions and defined roles and responsibilities. Each of these areas will be addressed individually.
Performance and Modelling of a Density-Based Autonomous Inflow Control Device
Authors: Corona G. , Greci S. , Novelen R. , Warren C. , Langaas K. 
Published: April 2024

Abstract
Autonomous inflow control devices (AICDs) are used to improve reservoir influx and restrict unwanted fluids for higher oil recovery. A new AICD has been developed to restrict water based on the density of downhole fluids. This is particularly useful in reservoirs where the oil and water have similar viscosities. This paper presents full scale flow performance results at reservoir conditions and modelling to predict the impact of this Density-AICD in well completions under various scenarios.
The Density-AICD is equipped with a novel Centrifugal Fluid Selector that magnifies subtle differences in buoyant forces and makes it orientation independent. The switching mechanism will autonomously adjust the choke to reduce the flow rate when changing from oil to water. A full-scale flow loop test was completed using a Norwegian oil crude sample and water at downhole conditions. The experiments evaluated the performance of the tool over different pressure differentials with single phase and multiphase fluid mixtures. To explore the impact of this device, a simple conceptual reservoir model was constructed.
The flow performance test results demonstrated that the tool produces oil at high flow rates and chokes water effectively. Two different nozzles sizes were tested proving the expected ratios of oil to water. It also confirmed the switching capability of the device to independently open and close based on the density contrast of the fluids. The multiphase testing showed the reversibility of the device and the water cut level necessary to close and open the device across a range of differential pressures.
The approximate behavior of this Density-AICD was implemented in an industry standard reservoir simulator. The model used realistic reservoir conditions from a Norwegian sub-sea development. The study shows that the Density-AICD can significantly decrease tail-end water production and further increase oil recovery across most reservoir scenarios.
The Density-AICD's self-adjusting feature simplifies and addresses uncertainties in the reservoir to restrict water, enhance oil recovery, optimize reservoir management, reduce water treatment costs at surface and contribute to reduced carbon intensity.
This paper publishes new flow performance test data for the Density-AICD using a Norwegian crude oil sample at representative downhole conditions. The conceptual reservoir modelling indicates a possible step-change autonomous inflow control technology that enables more carbon-efficient reservoir management.
EOS Modelling of Export Sales Products & Water of Condensation Bringing Value to a Mature Gas Condensate Subsea Asset in the North Sea
Authors: Mogbo Obuekwe 
Published: April 2024

Abstract
TotalEnergies operates four offshore fields in the West of Shetlands area. Traditionally, Black-oil based reservoir models linked to an integrated asset model (IAM) were used capture the reservoir-to-plant fluid dynamics in these mature, turbiditic, gas condensate fields produced through a long subsea tieback.
The project incorporated EOS modeling into the operational framework to engender multifaceted advantages. Firstly, it empowered asset managers with accurate predictions of water of condensation behavior, enabling optimized flow assurance measures to mitigate issues like hydrate formation and pipeline plugging. Secondly, the refined modelling of hydrocarbon composition improved the capacity of tailoring production techniques to maximize yields of Export Sales products. Additionally, compositional simulation methods enabled prediction of the backout impact on both a volume and energy basis, allowing finer computation of the economic impact of third-party tie-ins.
The EOS lumping was designed to replicate major sales products (LPG, Condensate etc.) and was further modified, introducing water as an EOS component in order to capture the water condensation phenomenon. Water vapor was introduced into the initialized reservoir Fluid Column without compromising earlier fluid properties matched to PVT lab observations, allowing wells to produce this water element as part of the liquid stream after condensation. A plant pseudo process was established from Process Flow Diagrams and historical plant pressure and temperature conditions were applied via periodic updates in the IAM.
The compositional simulation results were positive with excellent match to historical export sales products and water cut. Increased confidence in ability to predict condensed water allowed significant volume and cost optimization in MEG injected for Subsea Network Hydrate prevention. The enhanced accuracy in forecasting energy basis backouts vastly improved the economic assessments of third-party tie-ins.
In conclusion, this project underscored the value proposition of incorporating EOS modeling in a mature Gas Condensate subsea asset in the North Sea. By harnessing the power of EOS models, a mature asset could be managed with heightened precision, optimizing export sales products, ensuring flow assurance, and enhancing the modelling of economic returns. Such an enhanced physics approach modelling clearly contributes to extending the lifespan and economic viability of the aging offshore assets and also assists in making potential future investment decisions.
Revealing Microstructure and Enduring Properties of Settled Barite Extracted from an Offshore Well Two Decades Later – Well Abandonment and Slot-Recovery
Authors: Yousuf H. B. , Khalifeh M. M. , Saasen A. , Godøy R. , Karlsen H. C. , Naumann M. , Ibragimova Z. , Kruber C. , van Noort R. 
Published: April 2024

Abstract
Barite settling in the annulus behind the casing is an undesired yet common occurrence during the life of a well. Over time, the drilling fluid left in the annulus settles, leaving behind solidified barite that can hinder slot recovery and Plug & Abandonment (P&A) operations by impeding the cut and pull process. During a P&A operation, Equinor acquired settled barite samples from a North Sea well where the casing was held back by these weighting agents, introducing overpull and prolonging the cut and pull operation. A laboratory analysis program that included determination of the particle size distribution, electrokinetic potential of particles (zeta potential), crystallography (XRD), chemical composition (XRF), thermogravimetry analysis (TGA), and microstructure (QEMSCAN) was carried out on these settled barite samples to understand their properties. The results of this study provided valuable insights into the composition and characteristics of the settled material in the annulus. The solidified barite within the annular space exhibited no signs of chemical reactions. XRD analysis confirmed the barite to be the sole predominant solid in the solidified material, aligning with expectations. However, additional analytical techniques, including XRF, QEMSCAN, and Energy-Dispersive X-ray Spectroscopy (EDX) detected interconnections between barite particles, primarily facilitated by iron or quartz particles. Additionally, trace amounts of calcite, iron-oxide, SiO2, and mixed compositions involving Si, S, Fe, Ba, O, and Cl were identified within the solidified material. Scanning Electron Microscopy (SEM) results indicated that the particles exhibit strong compaction characteristics but lacked cementation, retaining some porosity. Notably, the absence of bentonite or other clays was consistently observed in all analyses. Furthermore, the zeta potential measurements of the samples showed a more stable response than the API barite. This study highlights the process of solidification observed in settled barite, suggesting that factors other than chemical reactions may be responsible for this phenomenon. The potential mechanisms contributing to solidification include physical aggregation, compaction, and alterations in surface charge under downhole conditions. This enhanced understanding of the solidification process will contribute to the development of solutions for efficient casing removal and even the utilization of settled barite as a barrier material.
A Digital Twin for Reservoir Simulation
Authors: Keilegavlen E. , Fonn E. , Johannessen K. , Tegnander T. , Eikehaug K. , Both J. W. , Fernø M. A. , Kvamsdal T. , Rasheed A. , Eigestad G. T. , Nordbotten J. M. 
Published: April 2024

Abstract
We have developed a physical room-scale porous media flow rig for operating, measuring, and visualizing reservoir flows in real time – the FluidFlower. The flow rig scale is large enough to achieve true multiphase flow effects (including phase mixture, gravity segregation and geological heterogeneities), while small enough to work on weekly time-scales, and allow for repeatable experiments.
Mirroring the FluidFlower, we have constructed a prototype of a digital twin for porous media flow – the PoroTwin. Essentially, we demonstrate that it is possible to achieve real-time transmissions of laboratory data from the FluidFlower to a cloud-based simulation- and machine learning environment, and complete the loop with applying optimal control algorithms to steer the experiment.
As part of the proof of concept, we also demonstrate that the machine learning environment can identify, and learn to correct for, incomplete physical descriptions within a reservoir simulator. The PoroTwin thus shows the potential of a fully integrated experimental and automated learning environment.
Enhanced Certainty of the Formation Boundary Location Through Novel LWD Interpretation Methods. Case Study from the Norwegian Continental Shelf
Authors: Nemushchenko D. A. , Krueger M. C. , Zaputlyaeva A. 
Published: April 2024

Abstract
Advanced geosteering methods are essential for effectively targeting complex reservoirs. Over the past decade, the utilization of Deep and Ultra-Deep Azimuthal Resistivity (DAR and UDAR) tools has significantly improved the accuracy of well placement. In conventional reservoirs, resistivity inversion results, calculated using DAR and UDAR data, have become a primary guiding factor for geosteering. Alternative methods such as stratigraphy-based geosteering are less commonly employed in conventional formations though they could provide low uncertainty interpretations of the well path location within the reservoir. This study demonstrates how stratigraphy-based correlation gives a thorough understanding of the lateral well location within a carbonate reservoir on the Norwegian Continental Shelf. Uncertainty in the interpretation is greatly reduced by the integration of geosteering interpretation methods, including inversion calculation from UDAR tools, and image log interpretation.
Achieving Water Shut Off (WSO) with Targeted Epoxy Injections in Open Hole Gravel Pack Subsea Gas Wells
Authors: Lootz K. , Sirevaag B. , Ciccarelli J. R. , Mirza D. , Ringe T. , Oddie K. 
Published: April 2024

Abstract
Methodology and results are presented for successful and unsuccessful zonal Water Shut Off (WSO) interventions for offshore subsea gas wells located in the Norwegian Sea with open hole gravel pack completions that do not have existing packers or other mechanical zonal isolation options outside of the screens. The field is produced by depletion and the water production needed to be halted to ensure the longevity of wells.
The operations were performed from a Riserless Light Well Intervention (RLWI) vessel. First the water producing zones were identified. Water was then isolated by perforating at a 3.5 m section of blank pipe between two production screens and epoxy was injected into the gravel pack to create an annular flow restriction between the formation and sand screen by use of an epoxy injection tool. Shortly after the epoxy cured, a bridge plug was installed on the inside of the screens at the same depth. The WSO depth had to coincide with a local reservoir pressure boundary such as a sealing shale.
The same WSO method was performed on three wells. These wells have produced between 1 and 4 million m3/d of gas, one well had water production from the first day of production and the other wells developed water after months of production resulting in water rates between 120-1000m3/d. Each well had varying levels of gravel pack quality between 50-100% and varying length/tortuosity; these factors became crucial to the success of the operation. All three wells will be discussed where 2 out of 3 of the wells had successful WSO with formation water eliminated from production. The interventions have extended the lives of all the wells by reducing fluid column weight (due to declining pressure) and boosting gas production given the water handling limitations of the facility. Two of the wells had such high water production and crossflow when shut in that they were expected to die within weeks without any further action by these interventions (refer to Table 1). Continued water production also decreased the viability of other wells in the same flow line, due to the subsea layout and associated limitation on maximum water handling capacity due to water increase.
The operation was performed on 3 wells and the learnings and planning was taken from one well onto the next, improving with each iteration. The gathering and use of all subsurface and well/intervention disciplines with all available data to decide on best shut-off locations was key to the success of these interventions.
A New Automated Workflow for Well Monitoring Using Permanent Pressure and Rate Measurements
Authors: Shchipanov A. , Cui B. , Starikov V. , Muradov K. , Khrulenko A. , Zhang N. , Demyanov V. 
Published: April 2024

Abstract
Pressure and rate measurements are essential for the well and reservoir surveillance workflows used in petroleum, geological carbon storage, and geothermal industries. Such well monitoring data are now analyzed in manual, semi-automated and automated modes or in a combination. Automated workflows are widely adopted by the industry nowadays, enabling most efficient knowledge extraction from the data both already accumulated and being received in real-time.
The paper describes a new integrated workflow for automated well monitoring using pressure and rate measurements obtained with permanent gauges and flowmeters. The workflow is based on time-lapse Pressure Transient Analysis (PTA) and integrates the following components: virtual flow-metering, transient identification, feature extraction and pattern recognition in transient pressure responses, and assessment of well performance based on PTA-metrics. The methodology behind the workflow combines different physics-informed and data-driven methods described in the paper. Application of the workflow is illustrated on a field case example from the Norwegian Continental Shelf, where changes in the well, reservoir, and well-reservoir connection performances are automatically monitored during its three-year long injection history. Reliability and accuracy of the automated monitoring results are verified via comparison with the conventional model-based time-lapse PTA.
The automated workflow may be used for a variety of use cases. Being applied to the well history, the workflow enables establishing a historical performance profile and identifying trends and issues in the past. In everyday well monitoring, it may be employed to detect well performance issues early and indicate their possible reasons. Further, it may provide valuable input for in-depth model-based analysis and other reservoir engineering studies. Using the workflow unlocks knowledge hidden in abundant well-monitoring datasets available at operating companies and empowers reservoir engineers to instantly assess well and reservoir performances, understand their interconnectivity, and make prompt, informed decisions.
Impact of Intermittency on Salt Precipitation During CO2 Injection
Authors: Landa-Marbán D. , Zamani N. , Sandve T. H. , Gasda S. E. 
Published: April 2024

Abstract
We study the effect of different parameters such as injection rate, permeability, and capillary pressure (grouped as capillary number) on salt precipitation and CO2 propagation within the reservoir during intermittent injections. Recent development in the open-source OPM Flow simulator allows to include salt precipitation in CO2 storage simulations. The logarithmic extension for the capillary pressure curve on the dry-out zone and the Killough model for hysteresis are adopted. To set up the reservoir grid, schedule in the injection, and rock and fluid properties, we have developed an open-source framework in Python. Then, the setting of the simulations is achieved via a configuration file that allows not only for reproducibility of the presented results, but to simulate additional scenarios. We show a comparison to published results using TOUGH2, resulting in a good agreement between both simulators. We present a sensitivity study where the impact of different modelling choices (e.g., using a well model where the flow is uniform, or the flow adapts to the reservoir connectivity) is assessed. Simulations in heterogeneous layered systems using the facie properties from the recent SPE CSP11 problem definition is also presented. Finally, the effect of alternating injection/shut-in periods (1 year per period) is assessed for the same amount of injected CO2 in a time frame of eight years, resulting in 35 cases starting with CO2 injection. The results reveal that during more extended shut-in periods, salt precipitation is happening closer to the wellbore which confirms the effect of capillary pressure on imbibing more brine into the dried regions. Quantities such as solubility trapping and the integral of the well bottomhole pressure over time (used as an energy proxy) highly depend on the intermittency pattern.
On-Chip Power Source Using Optimized On-Chip Solar Cells Based on a Standard Bulk CMOS Process for Single-Chip Self-Powered Smart Microsensors
Authors: Liu Jingjing , Guan Jian , Mo Wenji , Xiong Bingjun , Sun Kangkang , Yan Feng , Li Zhipeng , Choubey Bhaskar 
Published: April 2024

Abstract

Enhancing the photoelectric conversion efficiency of on-chip solar cells is important for the realization of self-powered smart microsensors. The surface electrode models for the on-chip solar cell based on CMOS process is constructed. It is verified by simulations and measurements that square ring electrode (RE) and center electrode (CE) don’t cause significant differences in the internal resistance of solar cells. Adopting the CEs instead of the REs can significantly reduce the shadowing effect of surface electrodes. To solve the problem of light blockage caused by the metal interconnections in the segmented solar cells, highly doped regions are used to replace some of the metal interconnections. A 0.01mm2 segmented triple-well on-chip solar cells with the CEs and highly doped region as interconnection is fabricated using a standard 0.18μm CMOS process. Measurement results show a 25.79% photoelectric conversion efficiency under solar simulator illuminations and has a 17.49% improvement compared to the conventional design. Utilizing the proposed solar cells, an on-chip energy harvesting power source has been realized, achieving a maximum conversion efficiency of 10.20% from incident solar power to voltage output power. Despite variations in illumination and load, this power source is able to maintain a relatively stable output voltage of 1V.