bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data Driven Risk Analysis and Production Forecast Deration for Matrix Bypass Events in the West Sak Oil Pool, Alaska North Slope
Authors: Keith Cody D , Abbas Sayeed , Autry Sydney 
Published: May 2023

Abstract
West Sak is a shallow viscous oil reservoir located partially within the Kuparuk River Unit on the North Slope of Alaska. The poorly consolidated reservoir is prone to sand production, leading to a significant risk for the development of void space conduits, locally known as matrix bypass events (MBEs). MBEs result in pattern breakage and lost production capacity, and this needs to be accounted for in production forecasting. In this study, a data-driven analysis is performed to identify factors that cause differential risk for MBE formation in each well. This analysis is then used to inform the creation of a tool that determines the expected production impacts of future MBEs and derates the forecast accordingly. The well patterns and MBE history in the West Sak reservoir are analyzed for differential risk based on sand geomechanics and producer/injector well completions. Specifically, the B sand was found to have the highest MBE risk due to its lower geomechanical strength, the D sand was found to have a significant yet lesser risk, and the A sand was found to have negligible risk. MBE risk is greater for patterns with horizontal production laterals without sand control and is negligible for horizontal producers with sand-exclusion screens or vertical producers. MBE risk is reduced when vertical injectors are used instead of horizontal injection laterals. This history is used to inform the development of MBE risk type curves based on the fatigue life distribution family of curves. These curves are used as input into an MBE deration forecasting tool, which produces a range of risk-informed MBE schedules. Based on each schedule, the tool "breaks" and "repairs" patterns accordingly, determining production losses based on allocation to each pattern. These individual production loss forecasts are then averaged to provide the expected outcome for forecast deration attributed to MBEs. The tool was successful in developing reasonable deration expectations on a well-by-well basis. The work done offers a probabilistic workflow to predict well downtime due to MBEs. Data-driven evidence is provided for factors that influence MBE risking, providing a means to capture expected production losses. This evidence proves to be consistent with physical models of this enigmatic phenomenon and informs future development opportunities to mitigate this risk. The approach pursued here can be applied to other known risks to production.
High Resolution Modeling of Pore Pressure Change, Fault Slip Potential and Induced Seismicity in the Fort Worth Basin
Authors: Yao Changqing , Park Jaeyoung , Chen Hongquan , Datta-Gupta Akhil , Hennings Peter , Dommisse Robin 
Published: May 2023

Abstract
The seismicity rate in the Fort-Worth Basin, north-central Texas, increased significantly from 2008. Previous studies attributed the seismic events to pore pressure increase caused by wastewater injection into the Ellenburger Formation. However, hydrocarbon production from the overlying Barnett Shale was not included in those previous studies. This study introduces a basin wide 10 year modeling and analysis of pore pressure change, fault slip potential and regional seismic events in the Fort-Worth Basin considering all production and injection activities.
In order to better understand the controlling mechanisms of induced seismicity and its relationship to hydrocarbon production and water disposal, a 3D heterogeneous basin model, which incorporates all available well log data, stratigraphic data from more than 1200 wells and petrophysical analysis of 47 wells is constructed. The high resolution 90 million cell model is first upscaled using a combination of layer and areal coarsening scheme to improve simulation efficiency and then calibrated using a streamline-based inversion method with the bottom-hole pressure of 122 injection wells. The history matching period includes injection volume history and production history of more than 18000 producers for over 10 years. Next, we performed 3D fluid flow simulation on the calibrated upscaled model from which basin-wide pressure distribution was generated. Finally, fault slip potential of all the interpreted faults are calculated based on pore pressure results and fault framework model to analyze the controlling mechanisms of seismic events in the Fort Worth Basin.
There are five main seismicity sequences in the Fort Worth area, which are DFW Airport Earthquake (2008), Cleburne Earthquake (2010), Azle Earthquake (2013), Irving Earthquake (2014) and Venus Earthquake (2015). Based on the pore pressure results from fluid flow simulation, all earthquake sequences, except for the Azle earthquakes, were found to be triggered by pore pressure increase. We previously proposed a different controlling mechanism for the phenomenon observed in Azle area, which is the unbalanced loading on two sides of a critically stressed fault. The results from this study are consistent with the previous findings. Fault slip potential calculations further validate the correlation between seismic events and pore pressure increase due to wastewater injection. By plotting the cumulative distribution of fault slip potential of all faults in the basin, we could identify the faults which are most likely to slip and trigger earthquakes.
The novelty of this work is basin-wide identification of mechanisms of induced seismicity considering hydrocarbon production and fluid injection using basin scale high resolution fluid flow modeling and streamline-based inversion of pressure history.
A Comparative Enhanced Oil Recovery Study Between Low-Salinity Water and Hybrid Surfactant Process for a Carbonate Reservoir
Authors: Belhaj Ahmed Fatih , Fakir Shasanowar Hussain , Singh Navpreet , Sarma Hemanta Kumar 
Published: May 2023

Abstract
Over the years, water-based enhanced oil recovery (EOR) techniques have continuously been of interest for their superior technical and economic feasibility. Low-salinity water (LSW) flooding is an attractive EOR method as it can significantly improve the performance of the conventional waterflooding process all while being financially feasible at a reduced cost. Regardless of its widely acclaimed efficiency, its incapacity to substantially alter the fluid–fluid properties in the reservoir remains as one of the critical limitations of LSW flooding. The hybrid application of low-salinity water with surfactant (LSS) is a novel EOR approach with great efficiency in lowering oil-water interfacial tension (IFT) and altering the rock surface wettability. In this study, an extensive comparative analysis is held between LSW and LSS on a carbonate rock to evaluate the extent of the improvement achieved via the addition of the surfactant to the low-salinity water system. The experimental analysis between LSW and LSS is compiled based on the evaluation of fluid-fluid and rock-fluid interactions. The fluid-fluid interactions were assessed using IFT tests. The IFT between LSW and LSS solutions and crude oil was measured using the spinning drop tensiometer. The rock-fluid interactions were examined using zeta potential experiments, reservoir-condition HPHT coreflooding experiments in composite cores, and contact angle measurements in an exclusive and specifically-designed HPHT imbibition cell. The results of the IFT tests showed more effective oil-water interactions of the LSW when the surfactant was added to 1%diluted-seawater (1%dSW). IFT measurements of LSS solutions displayed significantly lower values which were substantially lower than LSW solution. The zeta potential experiments using the streaming potential method showed a clear trend of yielding more negative values for LSS solutions versus LSW at 1%dSW. The contact angle measurements confirmed a 17° difference for LSS when compared to LSW. These outcomes demonstrated that the wettability of the carbonate rock was altered from oil-wet to intermediate-wet with the addition of a low concentration of the surfactant. Coreflooding data proved conclusively that the addition of 0.2wt% of the surfactant to the LSW flooding yielded an additional 9.11% of oil recovery. The comprehensive experimental work followed in this study including contact angle and coreflooding data under HPHT conditions and zeta potentiometric studies on surface charges using whole brine-saturated cores make the findings more representative of field conditions. This paper is aimed to improve the understanding of the ability of a surfactant to improve the fluid-fluid interactions and alter the rock-fluid properties when added to LSW flooding.
Dynamic Physics-Guided Deep Learning for Production Forecasting in Unconventional Reservoirs
Authors: Mohd Razak Syamil , Cornelio Jodel , Cho Young , Liu Hui-Hai , Vaidya Ravimadhav , Jafarpour Behnam 
Published: May 2023

Abstract
Neural network predictive models are popular for production forecasting in unconventional reservoirs. They have the ability to learn complex input-output mapping between well properties and observed production responses from the large amount of data collected in the field. Additionally, the flow behavior in hydraulically fractured unconventional reservoirs is not well understood making such statistical models practical. Variants of neural networks have been proposed for production prediction in unconventional reservoirs, offering predictive capability of varying levels of granularity, accuracy and robustness against noisy and incomplete data. Neural network predictive models that incorporate physical understanding are especially useful for subsurface systems as they provide physically sound predictions.
In this work, we propose a new Dynamic Physics-Guided Deep Learning (DPGDL) model that incorporates physical functions into neural networks and uses residual learning to compensate for the imperfect description of the physics. The new formulation allows for dynamic residual correction, avoids unintended bias due to less-than-ideal input data, and provides robust long-term predictions. The DPGDL model improves upon a static formulation by utilizing a masked loss function to enable learning from wells with varying production lengths and by improving the results when partially-observed timesteps are present. We also develop a new sequence-to-sequence residual model to correct additional biases in the long-term predictions from the physics-constrained neural networks. Several synthetic datasets with increasing complexity as well as a field dataset from Bakken are used to demonstrate the performance of the new DPGDL model.
Prediction of Single Proppant Terminal Settling Velocity in High Viscosity Friction Reducers by Using Artificial Neural Networks and XGBoost
Authors: Ge Xiaojing , Lu Rong , Biheri Ghith , Imqam Abdulmohsin , Bai Baojun 
Published: May 2023

Abstract
High viscosity friction reducers (HVFRs) have been recently gaining more attention and increasing in use, not only as friction-reducing agents but also as proppant carriers. The settling velocity of the proppant is one of the key outputs to describe their proppant transport capability. However, it is influenced by many factors such as fluid properties, proppant properties, and fracture properties. Many empirical/physics-based models and correlations to predict particle settling velocity have been developed. However, they are usually based on certain assumptions and have applicable limits. In contrast, machine learning models can be considered as a black box. The objective of this study is to use machine learning models to find the relationship between the multiple factors mentioned above and particle settling velocity in order to correctly predict it. Two of the most popular and powerful machine learning algorithms, Artificial neural networks (ANN) and XGBoost, were comparatively investigated with standard data processing and training procedures. Mean Absolute Errors (MAEs) for ANNs and XGBoost were 0.010379 and 0.004253 respectively. The XGBoost learning algorithm had overall better prediction performance than the ANN model in terms of the data sets used for this study and had the potential to properly handle missing values by itself.
What Did We Learn from SAGD Applications in Three Decades, and What is Next?
Authors: Pratama Randy Agra , Babadagli Tayfun 
Published: May 2023

Abstract
Steam-assisted gravity drainage (SAGD) has proved to be a technically and commercially successful methodology for recovering heavy-oil in Canada. At present, there are 22 commercial SAGD projects with over 300 pads and 2,700 well pairs, contributing to nearly 1.4 million bbl/day of production. The steam growth in the steam chamber could recover up to 60% of the oil-in-place by a typical SAGD project. However, some SAGD projects are only able to present less than 20% of the recovery factor, even though they have been producing for almost decades. Currently, the steam-to-oil ratio (SOR) for most SAGD projects ranges between 2 and 4 bbl steam/bbl oil. Nevertheless, some projects are still experiencing SOR of over 4 bbl/bbl due to the aggressive steam injection.
Despite the efficacious evidence and enormous contribution to oil production, many questions regarding the current SAGD project performance are still rising. The process and execution are very complex and entail great operational excellence. The thermodynamic processes (heat transfer, wettability alteration), reservoir geology (thickness, vertical conformance, steam channelling), well designs (optimal placement of the pairs, well completions), and environmental concerns (GHG emission) are also limiting factors to be detrimental to SAGD performance. Some other techniques to recuperate heavy-oil and bitumen (e.g., co-injection)—in addition to the principal SAGD—have been insinuated and employed in the projects. The efforts only presented a 5–10% of success rate.
This paper focuses on extensive evaluation and analysis of the ongoing SAGD projects over the last three decades in Canada and what would be the forthcoming potential of mature SAGD. Lessons learned and limitations from historical and current SAGD applications based on the evaluation of 22 commercial SAGD projects are presented. Success and failure stories were evaluated from geological, technical, environmental, and operational points of view. The reasons behind the successful applications of existing SAGD practices were listed. In the end, suggestions were made as to the proper design of new SAGD projects and future practices in the matured fields.
Some new insights for the future of mature SAGD, including "zero emission" applications using solvents and reduced emission using steam additives, are also discussed. The conclusive analyses done and the recommendations made will lead to more efficient SAGD applications (new and matured) in Canada, also providing a useful road map for the other parts of the world.
Nanoparticles for the Transport of Fluids in Porous Media
Authors: Yurukcu Mesut , Ozum Baki , Ziyanak Sebahattin , Saldana Jorge Leonardo , Yegin Cengiz , Yondemli Hande , Oskay Mehmet Melih , Temizel Cenk 
Published: May 2023

Abstract
Fluid transport can be improved by nanoparticles when they help stimulate a reservoir's rheological properties, which involve flow, viscosity, and permeability, among other parameters. First, this work reviews the literature regarding nanotechnology in the oil and gas sector. Then, it examines a few potential nanoparticle applications that have shown varying degrees of potential to improve colloid transport mechanisms in porous media. This list includes, but is not limited to, magnesium oxide, zinc oxide, silver, silicon dioxide, pyroelectric nanoparticles, and carbon nanotubes, all of which help stimulate a reservoir, which in turn leads to better fluid transport and an enhanced rate of recovery.
The authors find that, compared to a baseline scenario that applies no nanotechnology, silicon dioxide, also known as silica, offers interesting advantages when used in laboratory settings. For example, in the case of low permeability limestones, silica helped transport fluids through the fractured rock at a better rate than without nanoparticles. Similarly, aluminum oxide shows the potential to improve rheological and filtration features inside a reservoir, stabilizing the flow of material from a well. Despite the high promise, however, it is still an early stage for field applications, where only a few trials for the use of nanoparticles have been experimented with, especially in porous media.
Nanotechnology has become a favorite topic of research across many disciplines. This work is one of the first to offer a comprehensive look at the literature on nanoparticles in the oil and gas industry while also reviewing the applications of different ultrafine elements and their potential for future research endeavors in reservoir optimization and fluid transport in porous media.
Modeling Two-Phase Flow Behaviour in a Shale Gas Reservoir with Complex Fracture Networks and Flow Dynamics
Authors: Zhang Yunhao , Yang Daoyong 
Published: May 2023

Abstract
In this work, a robust and pragmatic method has been developed, validated, and applied to describe two-phase flow behaviour of a multifractured horizontal well (MFHW) in a shale gas formation. As for a fracture subsystem, its permeability modulus, non-Darcy flow coefficient, and slippage factor have been defined and embedded into the governing equation, while an iterative method is applied to update the gas/water saturation in each fracture segment within discrete fracture networks. For a matrix subsystem, a skin factor on a fracture face is defined and introduced to represent the change in relative permeability in the matrix domain at each timestep, while the adsorption/desorption term is incorporated into the diffusivity equation to accurately calculate the shale gas production by taking the adsorbed gas in nanoscale porous media into account. Then, the theoretical model can be applied to accurately capture the two-phase flow behaviour in different subdomains. The accuracy of this newly developed model has been confirmed by the numerical simulation and then it is extended to field applications with excellent performance. The stress-sensitivity, non-Darcy flow, and slippage effect in a hydraulic fracture (HF) are found to be obvious during the production, while the initial gas saturation in a matrix and HFs imposes an evident influence on the production profile. As for an HF with a high gas saturation, the dewatering stage is missing and water from the matrix can be neglected during a short production time. For the matrix subsystem, a high-water saturation in the matrix near an HF can affect gas production during the entire stage as long as gas relative permeability in the HF remains low. In addition, the adsorption/desorption in the matrix subsystem can increase gas production but decrease water production. Compared to the observed gas/water production rates for field applications, the solutions obtained from the method in this work are found to be well matched, confirming its reliability and robustness.
Insights on Gas and Water Coning/Channeling Processes in a Fractured Carbonate Reservoir from Embedded Discrete Fracture Modeling
Authors: Vo Hai , Flodin Eric , Hui Robin , Earnest Evan , Trindade Marcia 
Published: May 2023

Abstract
Coning is the mechanism describing movement of water from an aquifer and/or gas from gas-cap into the perforations of a producing well. The interface between the fluid phases deforms into a cone shape if the reservoirs are relatively homogeneous. In fractured reservoirs, water/gas incursions can take the form of discrete channels through fractures that connect the water/gas zone to the wellbore. Coning/channeling tends to increase the cost of production operations and influences the overall recovery efficiency of oil reservoirs. The coning/channeling processes constitute one of the most complex problems pertaining to oil production. This study investigates coning/channeling in an Atlantic margin pre-salt fractured carbonate reservoir using Embedded Discrete Fracture Modeling (EDFM) to gain a better understanding of the processes in fractured reservoirs.
This study focused on a sector Discrete Fracture Network (DFN) that was used to create a full-field Dual Porosity-Dual Permeability (DPDK) model. The DFN was used to generate end member models that capture the range of connectivity, geometry, and heterogeneity of fracture systems thought to exist in the field based on well log and core analysis. The sector area of interest also included existing producers and injectors and future infill wells. The coning/channeling phenomena were modeled using the EDFM method. The models were flow simulated using representative initialization, field management logic, and well producing rules, based on the history-matched full-field DPDK model. Mitigation methods to reduce coning impacts were also investigated.
EDFM, which represents the fracture network explicitly, provides insight on gas and water coning/channeling processes in a fractured carbonate reservoir. We find that fractures can lead to local channeling and coning. The degree of channeling and coning is a function of flow rates, fracture properties, and matrix-fracture exchange which in turn depends on rock property contrast between matrix and fractures. If matrix permeability is sufficiently high, matrix-fracture exchange is significant and fractures can act like leaky pipes. The effect of local gas coning/channeling is stronger in cases of isolated fractures surrounded by lower permeability rock. Water and gas coning can occur at the same time and interact with each other. Mitigation methods such as reducing well rates and use of selective completions can be applied to manage the gas and water coning/channeling.
Application of a Novel Green and Biocompatible Clay Swelling Inhibitor in Fracturing Fluid Design
Authors: Murtaza Mobeen , Tariq Zeeshan , Kamal Muhammad Shahzad , Rana Azeem , Patil Shirish , Mahmoud Mohamed , Al-Shehri Dhafer 
Published: May 2023

Abstract
Clay swelling and dispersion in tight sandstones can have an influence on the formation's mechanical properties and productivity. Hydraulic fracturing is a typical stimulation technique used to increase the production of sandstone formations that are too compact. The interaction of clay in sandstone with a water-based fracturing fluid causes the clays to disperse and swell, which weakens the rock and reduces its productivity. Several swelling inhibitors, including inorganic salts, silicates, and polymers, are regularly added to fracturing fluids. Concerns linked with these additions include a decrease in production owing to formation damage and environmental concerns associated with their disposal. In this study, we introduced naturally existing material as a novel green swelling inhibitor. The performance of the novel green inhibitor was examined by its impact on the mechanical properties of the rock. Acoustic strength and scratch tests were conducted to evaluate rock mechanical parameters such as unconfined compressive strength. Further inhibition potential was evaluated by conducting linear swell and capillary suction timer tests. The contact angle was measured on a sandstone surface for wettability change.
The results showed the novel green additive provided strong inhibition to clays. The reduction in linear swelling and rise in capillary suction time showed the inhibition potential and water control potential of the biomaterial. Furthermore, mechanical properties were lower than DI-treated rock sample tested under dry conditions. With all these benefits, using green novel additive makes rock more stable and reduces damage to the formation. The green additive is economical and an environment-friendly solution to clay swelling. It is an effective recipe for reducing the formation damage caused by clay swelling.