bluuebunny/crossref_metadata_2025 huggingface dataset:
Life-Cycle Gradient-Based Production Optimization Including Well-Shutoff Option with Least-Squares Support Vector Regression
Authors: Almasov Azad , Onur Mustafa
Published: October 2023

The objective of this work is to present an efficient method based on gradient-based optimization using a least-squares support-vector regression (LS-SVR) model to solve well-shutoff and well-control optimization problems. We formulate a continuous differentiable NPV for the well shutoff optimization problem. In our approach, switching well on/off times are considered part of the design variables. Our parameterization is based on a fixed number of cycles, the length of each cycle, and the production time fraction in each cycle. The remaining fraction of each cycle is the shutoff time fraction. We use linear equality constraints so that the summation of the length of each cycle is equal to the life of the production, and thus, we do not need to truncate the length of the last cycle. We consider both the stochastic simplex gradient optimization and the machine learning-based least-squares support vector regression (LS-SVR) proxy but we update it during optimization so that the updated proxy remains predictive toward promising regions of search space during the optimization. We compare the performance of the proposed method using the LS-SVR runs coupled with iterative sampling refinement method (ISR) to update the proxy during optimization with the popular stochastic simplex approximate gradient (StoSAG) and reservoir- simulations runs for a synthetic example considering a waterflooding process in a conventional compositional oil reservoir with 2 water injectors and 4 producers. Results show that higher computational efficiency is achieved using the LS-SVR-based optimization method over the StoSAG-based optimization method using a high-fidelity numerical simulator. The proposed LS-SVR-based framework is shown to be at least 3 to 7 times computationally more efficient, depending on the cases considered than the StoSAG using a high-fidelity numerical simulator. For the waterflooding optimization example, designing multiple shutoffs and making cycle length unknown are found to be not beneficial as compared to single shutoff cases as they yield lower NPVs than single shutoff cases. However, we observe that the size and sampling of the training data, as well as the selection of bound constraints for the well controls, influence the performance of the LS-SVR-based optimization method. The well-shutoff/well-control optimization problem can be handled with the gradient-based optimization methods by introducing a production time fraction as the design variable for each cycle. This is the first LSSVR application for the well shutoff and well-control optimization problem. The proposed LS-SVR-based optimization framework has great potential to be used as an efficient tool for this type of optimization problem.
Review of Downhole Gas Liquid Separators In Unconventional Reservoirs
Authors: Al Munif E. H. , Alhamad L. , Ejim C. E. , Banjar H. M.
Published: October 2023

The accumulation of liquid in deeper wells poses a critical problem as it significantly reduces the well's productivity index. One of the methods used to lift the accumulated liquid is the sucker rod pump system (SRP). However, lifting large volumes of liquid and associated gas to the surface artificially has been challenging, particularly with rod pump systems. To address this issue, a downhole gas separator can effectively be deployed below the pump intake to separate the free gas from the produced liquid. The gas separated downhole can then be extracted through the tubing-casing annulus while the liquid is artificially lifted through the tubing. The paper endeavors to provide a comprehensive review of recent advancements, technologies, and challenges related to downhole gas-liquid separators. The findings of this study can serve as a valuable guide for the development of downhole gas-liquid separation technologies in the industry, particularly for installation in unconventional wells.

This review includes various laboratory evaluation tests and field examples that outline the efficiency and reliability of some downhole gas-liquid separators. There are two approaches implemented to design separators. The first approach is called static gas separation, based on the gravity principle. The second approach is dynamic gas separation, which is based on applying centrifugal forces through rotational speed. However, several downhole gas-liquid separators have low efficiency and lack an acceptable guideline for their optimum design. In some fields that suffer from liquid loading problems, it may be imperative to design and install an SRP and a downhole gas-liquid separator, to prevent gas lock problems.

Based on the reviewed literatures, it was shown that centrifugal separators had better gas/liquid separation efficiency comparing to gravitational separators. Cyclone centrifugal separators consistently exhibit separation efficiencies ranging from 90% to 98%, whereas gravity-based separators typically achieve efficiency levels between 70% and 90%, depending on the design and operational variables. Centrifugal separators consistently deliver exceptional separation efficiencies, with effectiveness ranging from 90% to 99%. Moreover, the swirl tubes have showcased an approximate separation efficiency of 90% and effectively handle the fluctuating gas flow rates encountered in the well.

This review comprehensively examines the advancements, limitations, and applications of downhole gas-liquid separators in oil and gas operations, specifically in conjunction with artificial lift systems. The paper aims to bridge the gap and differentiate between different types of downhole separators, offering researchers an extensive guide for their current and future investigations. Additionally, it proposes suitable technologies that can be deployed alongside the sucker rod pump (SRP) to enhance its efficiency in wells facing challenges related to liquid loading.
Best Practices for Building a Modern and Resilient Supply Chain Framework in the Oil and Gas Industry
Authors: Sharma Akash , McDonald Dan
Published: October 2023

The oil and gas industry operates in a complex and challenging environment with significant supply chain management risks. This paper aims to provide a comprehensive review of these risks and proposes strategies to create a best-in-class supply chain practice using Industry 4.0 technologies. With energy prices being highly volatile and the macroeconomic situation created by COVID-19, having a resilient and robust supply chain practice is essential for oil and gas operators. The paper emphasizes the need for the energy industry to shift its view of the supply chain from a tactical, reactive organization to one of strategic value.

To establish a best-in-class supply chain practice, the paper discusses the integration of various Industry 4.0 technologies, such as artificial intelligence, robotics, and automated systems. The authors suggest leveraging tools such as spend analytics and data modeling to make informed decisions and automate dispatch processes, leading to positive fiscal and ESG impacts. They also emphasize the critical role of automation of the payables process and real-time visibility of validated invoice line-item cost detail data to achieve a should-cost modeling environment. The authors propose a manage-by-exception model that focuses on operations, value creation, process improvement, and automation of redundant support functions to mitigate risk and provide a competitive advantage for the entire enterprise. The paper presents novel and additive ideas for modernizing the oil and gas supply chain.
Sand Detection Using Acoustic Sand Monitors for Liquid-Dominated Multiphase Flow Production
Authors: Nadeem Asad , Vieira Ronald E. , Shirazi Siamack A.
Published: October 2023

Solid particle erosion in the oil and natural gas industry can be damaging to pipes fittings and equipment, which can lead to maintenance or in the worst case a production shutdown. In both cases, this represents a huge economic loss for the industry. Acoustic sand monitoring is one of the most widely used practices to estimate the amount of sand in the flow. In addition to being commercially available, they can be easily clamped to the outside of a pipe wall, measuring the acoustic energy generated by sand grain impacts on the inner side of a pipe wall. In this work, a broad range of multiphase operating conditions has been experimentally investigated with acoustic sand monitors in large-scale flow loop facilities to determine the effectiveness of sand monitoring in liquid-dominated multiphase flow. The main objective is to use acoustic sand monitors to determine the Threshold Sand Rate (TSR). This is the minimum sand rate necessary to achieve monitor output higher than the background noise level. Acoustic monitors were placed upstream and downstream of standard (r/D = 1.5) elbows while varying superficial gas and liquid velocities, sand size (25, 75, 150, 300 and 600 micron), pipe diameter (2-inch and 3-inch) in vertical orientation. The experimental conditions were selected to cover slug-churn, dispersed-bubble flow and liquid-sand flow conditions. These results are compared to the previously obtained test results on 50.8 mm (2-inch) ID test loops.

The TSR results for liquid-dominated multiphase flow regimes are determined experimentally. The effects of sand size and flow regimes on TSR had been obtained. In 50.8 mm (2-inch) threshold limits were observed for dispersed-bubble flows regimes and liquid-sandas compared to gas-dominated flow conditions. While TSR is highest in dispersed-bubble flows regimes. The present data was compared to previous results obtained for annular, slug and stratified flow patterns in vertical flow. It was observed that the annular flow regime has the lowest TSR values showing an increase in TSR when the liquid rate increased. The results from this work can help operators understand how acoustic monitors can detect and distinguish sand impact noise from the background flow noise in liquid-dominated multiphase flow in production facilities. In this way, greater assurance is provided to operators for optimizing oil and gas production rates, especially in wells that tend to produce solids.
FluidMagic: A Sophisticated Allocation Solution for Tackling Production Technology Challenges in the Gina Krog Field
Authors: Castillo J. Reyes , Uleberg K.
Published: October 2023

This publication is aimed to show the potentiality of FluidMagic, an Equinor in-house developed software tool, for analysis, decision making, and production follow up. The tool was proven to be successful in differentiating from the gas in solution, gas condensate and injection gas produced by wells, and at the same time, it was able to provide estimates of the proportion of free reservoir oil produced in the Gina Krog field in the Norwegian Continental Shelf. Developed in Python, this innovative software tool is powered by a sophisticated regression algorithm that recombines and modifies the reservoir fluids to match reported test separator volumes and densities. Individual well downhole pressure and temperature, as well as fluid rates from test separator and measured gas-lift rates are used as input. FluidMagic outcomes were validated by a compositional reservoir numerical simulation model used to generate synthetic test separator data. For this purpose, the gas tracer option was enabled to track the produced injection gas fraction. Results showed a perfect conversion from test separator rates to process rates, along with a near perfect estimation of well stream flowing compositions. In addition, remarkably accurate allocation of reservoir fluid and injection gas production was achieved.

Early gas breakthrough in Gina Krog oil wells had been observed just months after production start-up and even before gas injection started. This created challenges when it comes to computing the amount of gas being recirculated throughout the oil producers with high GOR. Estimating recycled gas amounts became crucial to maximize the free reservoir oil production from the oil rim and liquid production from the gas cap. FluidMagic then became the key enabler to utilize the massive amount of data collected daily from the test separator by allowing the quantification of the corresponding allocated surface oil and gas production from well stream. Implementation of FluidMagic in Gina Krog field have proven to be effective for: quantification of the injected dry gas volumes that had been back produced by specific wells in the field, in the determination of individual well stream composition, for evaluation of the well intervention (zone isolation) efficiency as well as for gas tracer breakthrough timing confirmation. This novel approach provides the ability to accurately allocate production at reservoir and surface level virtually at real-time based on daily production data from test separator, avoiding frequent updates to the rather complex and time-consuming compositional reservoir numerical model. Similarly, this methodology minimizes the need for frequent fluid sampling in connection to feed composition predictions.
Surveillance, Analysis, and Optimization (SA&O) During Active Drilling Campaign
Authors: Zhang Yanfen , Bovet Paul , Samano Lorelea , Isabu Ozzy , Chima Andres , Everson Erik , Sun Kai
Published: October 2023

Deepwater drilling is an expensive complex operation. Real-time surveillance data and analysis for drilling operations are very important for ensuring safety and cost control. Due to the high production rate and high expense of deepwater wells, there are usually not many wells planned for developing a deepwater field. Therefore, the results of each well hold particular significance as additional reservoir surveillance data and are crucial for optimizing field development and production forecasts.

The subject field of this paper is WRB (pseudonym) which is a deepwater field located in the Gulf of Mexico. In the past few years, about one to two new wells per year came online at WRB field. Thus, there has been a constant stream of surveillance data from both drilling new wells and production/injection at existing wells. All the surveillance data were processed and utilized for updating the reservoir simulation model that ultimately serves as the engine for optimizing the future well locations.

This paper is intended to review and share the key learnings and best practices of Surveillance, Analysis and Optimization (SA&O) during the active drilling campaign of WRB field. A comprehensive effort was undertaken to review the historic surveillance activities carried out during drilling and post-drill, and to review the consequent value-adding decisions from effective use of surveillance information.
Thermodynamic Modeling of Aqueous Nanobubble Dispersion
Authors: Achour Sofiane H. , Sheng Kai , Lawal Tesleem , Okuno Ryosuke
Published: October 2023

The amount of gaseous species in water or brine can be greatly enhanced in the form of nanobubble (NB) dispersion. Aqueous NB dispersion has vast industrial applications, potentially in enhanced oil recovery and carbon dioxide (CO2) sequestration to control the mobility of gaseous species. Development of such NB technologies depends on a proper understanding of thermodynamic properties of aqueous NB dispersion. The objectives of this research are to analyze the thermodynamic stability of aqueous NB dispersion and to apply a thermodynamic equilibrium model to analyze experimental data.

We first present a thermodynamic formulation for modeling aqueous NB dispersion, which clarifies that aqueous NB dispersion occurs in the aqueous phase that is supersaturated by the gaseous species in the system. That is, the gaseous species are present in two modes: dispersion of gas bubbles under capillary pressure, and molecule dispersion (supersaturation) in the external aqueous phase. Such a thermodynamic system is referred to as aqueous NB fluid in this research, and specified by (NC + 3) variables (e.g., temperature, total volume, components’ mole numbers, and capillary pressure), in which NC is the number of components. We then present a novel implementation of the GERG-2008 equation of state (EOS) in minimization of the Helmholtz free energy to solve for equilibrium properties of aqueous NB fluid. GERG-2008 was used in this research because it is suitable for modeling an aqueous phase that is supersaturated by gaseous species.

The thermodynamic equilibrium model was applied to experimental data of aqueous NB fluid with nitrogen (N2) at pressures up to 277 bara (4019 psia) and 295.15 K (71.6°F). Application of the model to experimental data indicates that a large fraction (0.8 – 0.9) of the total amount of N2 is in the form of molecule dispersion, but such supersaturation of the aqueous phase is possible because of the presence of NB dispersion with capillary pressure. That is, NB dispersion can increase the gas content in aqueous NB fluid by enabling gas supersaturation in the aqueous phase as a thermodynamic system. Although experimental uncertainties resulted in a possible range of equilibrium properties for aqueous NB fluids at high pressures, the extrapolation of the calculation results to atmospheric pressure yielded a radius and a number density of bubbles within the range of data reported in the literature.
Casing Design Load Case for Shut-In After Worst Case Discharge Using a Progressive Depth Analysis Approach
Authors: Howard J. A. , Grant L. , D'Amico R. , McSpadden A. R. , Kalil I. A. , Trevisan R. , Glover S.
Published: October 2023

The US Bureau of Ocean Energy Management (BOEM) defines Worst Case Discharge (WCD) as the maximum foreseeable daily flow of oil from a well, commonly referred to as a "well blowout." When casing design engineers refer to "WCD", they focus on the impact of shutting in a maximum flow case on casing stresses as opposed to "volume" of discharge. This is sometimes referred to as Worst Case Discharge Pressure (WCDP) or Maximum Discharge Casing Pressure (MDCP) or Worst Case Discharge Load (WCDL). The US Bureau of Safety and Environmental Enforcement (BSEE) may refer to this pressure as Pressure Gradient (PG). Some international operators refer to "WCD" only as a load case and not a discharge volume so the term "WCD" may mean different things to different people. A new approach is presented to augment casing design load methodology associated with shut-in of an openhole flow event and where multiple hydrocarbon zones are exposed in an openhole section.

The proposed methodology determines the casing design loads for the highest potential flowing temperature and highest shut-in at capping pressure case establishes stresses on the existing casing and verification of casing hanger lift-off. Uniform understanding and resolution of volume-based assessment and well survivability considerations in current practice are discussed. The Progressive Depth Approach focuses on determination of the highest stress by considering the progressive contribution of multiple reservoirs flowing during an uncontrol flow event and subsequently shut-in.

The load case is conceptually structured in two events: 1) uncontrolled hydrocarbon flow through exposed casing strings with related discharge to ambient conditions (seabed in subsea wells) and 2) shut-in of the well with capping installed at wellhead. From a casing design and well integrity viewpoint, the load case enables quantification of stress changes along existing casing strings and at the casing hanger to assess well survivability. Thermal effects typically generate compressive forces (hot cases) and induce annular fluid expansion in casing annuli (if sealed) potentially leading to hot casing collapse scenarios in combination with severe draw-down pressures in the inner wellbore. Axial forces generated at the casing hanger need careful evaluation relative to lockdown mechanism ratings in a subsea wellhead.

Operators may incorrectly assume that shut-in of the deepest reservoir in an open-hole section generates the highest stress casing load. Rather it could occur from a shallower reservoir depending on formation pressures, fluid composition and contribution of the remaining reservoir exposed (commingled fluid and flow conditions). An advanced load methodology to apply flow conditions and shut-in of an open-hole flow event given multiple reservoir zones for the determination of maximum thermal effect and shut-in pressure at capping wellhead condition is presented herein.
The Secrets to Successful Deployment of AI Drilling Advisory Systems at a Rig Site: A Case Study
Authors: Behounek Michael , Ashok Pradeepkumar
Published: October 2023

Developing artificial intelligence (AI)-based drilling advisory software is generally straightforward when good quality labeled data are available. However, deploying such systems in the field for use by a rig crew requires careful planning and execution and often fails to provide the value proposed. It is statistically estimated that most AI projects fail, and that most companies that trial AI solutions report minimal to no impact from AI. This paper details the successful deployment and ongoing success of an AI-based drilling advisory system on rigs across an Operator's fleet, as well as deployment decisions that helped make it a high-value, sustainable, and successful program.

The Operator developing and deploying the AI system focused on five main aspects to anchor this project: setting a realistic long-term vision for automation, choosing the right tools and techniques, implementing a targeted change management plan, careful selection of team members, and planning for sustained management support. For the longer-term automation vision, decisions on where to deploy the AI models - at the rig or managed from the central office, what parts of the solution to develop in-house or out-source to achieve cost objectives, and how soon to scale AI to all rigs in the fleet were key. Finally, a thoughtful change management plan was implemented taking into consideration the company culture and industry best practices.

The project launched in 2015, with the decision to deploy the AI models at the edge/rig site with an ability to push updates from a remote, central support group as needed. The AI model platform was outsourced; AI models were developed /validated one model at a time, and then deployed to all the rigs as soon as possible. The platform and models were modularized to enable rapid prototyping, field deployment, and iterative change. A key Program Sponsor along with other Stakeholders were identified for each rig, and carefully managed to ensure ongoing support, successful adoption, and regular feedback. Transparency on how the model performed calculations was shared readily to ensure acceptance of the results by the drilling engineers and the rig site crew. An agile development and deployment cycle was adopted to maintain rig crew interest to continuously use and improve the system. Over the past eight (8) years, more than ten (10) AI models have been added incrementally to the rig-based system, which has enabled a 10% improvement in drilling performance year over year.

This paper details the decisions and processes that resulted in the successful deployment of an AI-based drilling advisory system for rigs in North America and Europe. The learning and insights from this multi-year (8 years and ongoing) deployment should provide valuable insights to those planning to deploy AI software at scale, at the edge.
Causal Inference for the Characterization of Microseismic Events Induced by Hydraulic Fracturing
Authors: Conde Oliver Rojas , Misra Siddharth , Liu Rui
Published: October 2023

This study proposes a workflow that employs causal inference techniques on microseismic data acquired during hydraulic fracturing operations on 2 horizonal wells in Marcellus Shale. The study quantifies the causal relationships between a new microseismic event and the prior "spatiotemporally proximal" microseismic events, while taking into account the confounders that influence both the causes and effects. In doing so, we explain the magnitude, location, and occurrence of a new microseismic event produced during hydraulic fracturing as a consequence of the prior "spatiotemporally proximal" microseismic events. The causal relations quantified in this study are beyond statistical correlation/association tests. The study provides new insights into the microseismic-source mechanisms, such as: 1) Magnitude of a new microseismic event does not depend on the number and the spatial and temporal concentrations of the spatiotemporally proximal, prior microseismic events; 2) Regions with high microseismic magnitude events produce a new microseismic event earlier in time; and 3) Microseismically active regions produce a new microseismic event much earlier in time. Selection of true confounders is crucial for obtaining accurate causal estimates. Failure to properly select confounders can result in significant overestimation or underestimation of the causal estimates, as high as +/- 100%. Certain treatment-outcome pair exhibit large differences between the causal estimates and correlation coefficients that confirm the independence of causation and correlation. A causal analysis with true confounders reveals the true causal relationship that cannot be quantified using correlation/association methods.
HPHT Perforation Testing With Cesium Formate and Oil-Based Kill-Pills for North Sea
Authors: Le Guen Y. , Kumar A. , Jackson P. , McGregor J. , Grove B. , Rogers G.
Published: October 2023

A fluid with loss-control capability (kill pill) is used as the completion fluid during perforating to seal the formation immediately after perforating to maintain well control. This saves the time required to displace completion brine and the cost of losing the expensive brine into the formation. However, perforating with the kill fluid in the wellbore presents a great challenge in minimizing formation damage (Chang, Kageson-Loe, et al. 2004).

For wells requiring to be perforated with a static overbalance pressure (SOB) and subsequently shut in with the kill fluid in place (to maintain well control while retrieving the gun and installing the completions system), a properly designed dynamic underbalance pressure (DUB) should be used to surge all perforation skin damage (caused by perforation debris and grain crushing) out of the perforation tunnel and let the wellbore pressure recover back to overbalance rapidly. This sequence allows building of a thin yet effective kill-pill filter cake against the clean perforation tunnel wall (Chang, Mathisen, et al. 2005). Too little DUB could leave the perforations with significant perforation skin remaining, strongly impairing the productivity. Too much DUB has the potential to cause perforation cavities to collapse, which will also strongly impair the productivity.

Further, some kill fluids, such as a heavy brine formulated with cesium formate (CsFo) are significantly more costly than other kill fluids, such as an oil-based mud (OBM). Therefore, optimizing the perforating design and choosing the proper kill fluid are crucial tasks to ensure good well productivity (Chang, Kageson-Loe, et al. 2004).

This paper discusses how one North Sea operator conducted large-scale perforation and formation damage qualification testing of two perforating kill-pill candidates for use in completing HPHT wells located in the Central North Sea. Test program design, results, and implications are discussed. To the authors’ knowledge, novel information presented includes 16-hour shut-in leak-off responses, flow initiation differential pressure, and return cleanup flow data for kill-pills placed within real perforations (perforations created using a real explosive shaped charge), quantitative and qualitative descriptions (with photos) of resulting CsFo and OBM kill-pill external filter cakes, dye flow visualizations of production flow path into perforations having kill-pill filter cakes, and quantification of single-shot total perforation skin decomposed to effective crushed zone permeability and thickness.
Predicting Rig Engine Utilization Using Machine Learning to Drive Fleet-Wide Emissions Reductions Initiatives
Authors: Poludasu S. , Groh A. , Snijder van Wissenkerke M. , Harrist J.
Published: October 2023

With the drilling industry's focus on sustainability and digitalization, there are several data-driven studies published in the recent years which aim to reduce the operational fuel consumption and greenhouse gas (GHG) emission footprint through use of efficient generator management and alternative fuel sources. The possible savings from these optimization solutions are often measured with respect to a baseline - a model representing expected performance for the observed load profile. Since rig power demand and crew behaviors can vary immensely, estimating this baseline accurately can be challenging, while still being critical for GHG reduction initiatives to measure progress. This paper presents a novel data-driven methodology using machine learning to provide a real-time representative model of generator management.

Two years of generator power output data at 1 Hz sampling frequency was collected over 110 rigs for this study. From this data, multiple time-dependent features were created to capture and learn from trends in rig power requirements. An ensemble of rig-specific models was built using an ordinal classification algorithm to predict the number of generators online at any particular instant, while remaining true to the core behaviors across the fleet. Additional logic was added during testing to ensure results were realistic and interpretable by field personnel. This real-time model was then deployed to run on this contractor's edge-computing platform across its fleet of rigs.

Emissions metrics using the proposed methodology were one of the crucial results that encouraged the rig crews to reduce the fuel consumed over the duration of this study. These metrics were integrated into proactive reporting sent to rigs to improve their generator management practices and to highlight rigs with outstanding practices. Results on the impact of these initiatives on performance will be discussed.

The authors are not currently aware of any large-scale, data-driven approaches to estimating generator usage on drilling rigs. This approach offers new ways to assist and make an impact on fleet-wide GHG reduction initiatives. Additionally, the unique ensemble framework of this methodology can be customized and adapted easily to many applications involving timeseries prediction over multiple rigs / operating units. This paper also demonstrates the value of data monitoring and data-driven workflows in increasing the operational efficiency.
Electrical Treatment to Revive Dead Gas Wells due to Water Blockage
Authors: Aljuhani G. , Almuaibid A. , Ayirala S. , Qasim A. , Yousef A.
Published: October 2023

The occurrence of water blockage is a major concern for gas wells, which severely impacts the productivity. This phenomenon is due to the prolonged contact of surrounding region around wellbore with water thereby increasing the water saturation relative to gas saturation. Consequently, the pore spaces are completely occupied with water, blocking the flow of gas and thus reducing the gas production. In this paper, we propose electrical treatment as a potential solution to reverse the unforeseen water blocking process and revive dead gas wells to produce desired gas.

Electrical treatment involves the placement of two electrodes in between two spaced wells or within the same well, one acting as source and the other as a sink. One of these electrodes acts as a cathode, while the other as an anode to cover a reservoir region of around 2-3 km. After current is applied from power supply to well head, the charge will propagate through metallic casing along the well until pay zone delivering electric current to the reservoir. The electrical induced effects in the reservoir may vary according to the variation of the current density and voltage applied.

The tight and small pore throats will be enlarged by the application of electrical current. This results in an increase of pore throat radius due to motion of water molecules, cations and anions thereby releasing some of the water from blocked pore throats. Thus, permeability and subsequently relative permeability to water is increased. The local energy pulses will also cause partial electrolysis forming gas droplets besides enhancing the coalescence of released water droplets to form larger water ganglia. These larger water ganglia will sequentially grow to form a continuous film of water phase to minimize surface energy and ease the movement of water. The electrical treatment operation can take up to 30 hours with a long-lasting effect from 6 months up to 2-3 years.

The electrical treatment method described in this paper to revive dead gas wells is a sustainable and eco-friendly solution for easy practice in the field. This cost-effective approach can prolong the life of gas wells to increase the productivity.
Understanding Subsurface Uncertainty for Carbon Storage in Saline Aquifers: PVT, SCAL, and Grid-Size Sensitivity
Authors: Likanapaisal P. , Lun L. , Krishnamurthy P. , Kohli K.
Published: October 2023

Subsurface uncertainty has a great deal of impact on the development of oil and gas reservoirs, as demonstrated through decades of industry experience. Understanding uncertainty to facilitate robust business decisions across potential scenarios is the cornerstone of successful field development. Although carbon storage is also subject to subsurface uncertainty, the phenomena that impact storage efficiency may not be the same as those influencing oil and gas production. The objectives of this study are to utilize reservoir simulation to

Investigate how rock and fluid properties affect CO2 plume size, migration, and trapping mechanisms during- and post-injection, Perform grid size sensitivity to define resolution requirements, and Quantify the impacts of coarse simulation grid and the requirements of monitoring resolution.

We present how reservoir conditions (i.e., temperature, pressure, and salinity) affect fluid properties and carbon storage performance. Reservoir temperature and pressure are considered both independently and together along geothermal gradients. A similar investigation also provides the sensitivity result based on varying SCAL (i.e., relative permeability and capillary pressure) parameters. For the grid size sensitivity, the findings demonstrate that an accurate plume size requires a fine vertical grid resolution, while the areal grid resolution impacts the dissolution rate. We make gridding scheme recommendations for reliable predictions based on these findings. We also analyze the result to quantify the error due to coarser grid size and the requirements for appropriate monitoring resolutions.

The results from the sensitivity study can help categorize storage site potential. The grid size study provides crucial information to develop reservoir simulation best practices in evaluating carbon storage candidates. Another aspect of a carbon storage operation is the monitoring plan to ensure the containment of the injected CO2. Since the geometry of the plume continues to evolve post-injection, the simulated predictions can guide the selection of monitoring technology with appropriate resolution necessary to capture the CO2 plume at various timeframes.
Multizone Open Hole Gravel Pack Completion with Selective Production Capability in ACG Field – Azerbaijan
Authors: Susilo Yoliandri , Dharmadhikari Khsitij , Taha Sherif , Ismayilova Ayisha , Guliyev Ilkin , Jafarli Zaur , Kerimov Natig , Kerimova Ravana , Mammadov Elvin , Veliyev Samir , Wallace Alex , Whaley Kevin , Foster Mike
Published: October 2023

Azeri-Chirag-Gunashli (ACG) is a giant field located in the Azerbaijan sector of the Caspian Sea. The major reservoir zones are multi layers sandstone formations and weakly consolidated where Open Hole Gravel Pack (OHGP) completions have become the standard design for production wells. To date more than 170 high rate OHGPs have been completed that are producing comingled from multi-layered sandstone formation.

As the field matures, problems such as premature water and gas breakthrough are becoming increasingly common requiring the completion system to be inherently flexible to address such issues. The Multi Zone OHGP concept design has been developed to manage this increasing reservoir management complexity. Zonal isolation and selective production capability are achieved by installing combination of multiple Screen PBR and/or open hole packer in combination with seals unit and mechanical sliding sleeve in the inner string at the intermediate completion, and Inflow Control Valve (ICV) at the upper completion.

To date, two Multizone OHGP wells have been completed successfully. The Screen PBR system has proved to provide effective zonal isolation or baffling. This system allows flexibility to deal with unexpected reservoir surprise (wet/gas zone) that requires zonal isolation on day-1 without major changes in completion design, thus reducing rig time & operational cost.

This paper discusses design, execution, and result of the first two Multizone OHGP completions installed in the ACG Field. Installing multiple Screen PBR to provide baffling against crossflow is a novel concept. This technique does not compromise gravel pack quality or sand control integrity. The success seen with this technique makes a compelling case to further develop the concept on a larger scale in ACG and maximize field recovery.
Duplicate Detection of Technical Documents in Petroleum Context Based on Near-Duplicate Image Search
Authors: Maze Elie , Dirhoussi Amine , Vernaz Yann , Farahbakhsh Reza
Published: October 2023

Identifying technical document duplications is a crucial task to optimize storage resources and improve document management and retrieval processes. This helps to ensure that the most up-to-date version of documents is going to be available, which is important in all industrial domains including the petroleum sector to avoid errors and inconsistencies. In addition, deduplication is a key step to consider in data pre-processing for training large machine learning models. This paper tackles the task of duplicate detection in technical reports by proposing a hybrid solution based on open-source libraries on computer vision. The proposed solution has been evaluated on a large set of data and provided promising results which can help us to optimize our storage. We observed the solution is flexible enough to adapt to different scenarios and different types of reports. Having such a solution will potentially lead to reducing the carbon footprint in IT infrastructures.
Automatic Integration of While Drilling Cutting Descriptions with Formation Evaluation Models
Authors: Alakeely A. A. , Torlov V. S. , Qubaisi K. A. , Kanfar M. F.
Published: October 2023

The procedure of analyzing and integrating text information from cutting descriptions collected during drilling process with formation evaluation models is a tedious task that is demanding in terms of time and human labor. The work describes a process to automate the task and use it to identify hydrocarbon zones in exploration wells.

As the drill bit penetrates the formations in a well, the rock fragments are usually described across the associated depth of interest in a text format. These descriptions are valuable source of information that are usually compared to petrophysical models that uses wireline logs as input. In this work, textual cutting descriptions are utilized in identifying potential hydrocarbon zones using natural language processing and deep learning algorithms. The methodology uses natural language processing techniques to generate data set. The data set is used to train a deep learning algorithm to identify hydrocarbon zone from cutting descriptions automatically.

The system has been used to identify hydrocarbon zones in a group of exploration wells. The trained model has been applied to blind test wells. The methodology reached hydrocarbon detection accuracy of 98% in challenging areas. For example, it allows hydrocarbon detection in low resistivity pay reservoirs where Archie's based saturation calculations present a water wet zone. The result was confirmed by formation tester and testing results suggesting the correctness of the technique. Moreover, the automation reduces the turnover time of such analysis and reduces human error.

The enclosed process helps in integrating textual information into the petrophysical model to reduce uncertainty, human labor, and aid in identifying hydrocarbon zones. In addition, the method will reduce the need for unnecessary testing, resulting in cost saving in rig time operation.
Evaluation of Fluid Containment and Perforation Erosion in Multistage Fracture Treatment
Authors: Sakaida Shohei , Hamanaka Yasuyuki , Zhu Ding , Hill A. D. , Kerr Erich , Estrada Erick , Scofield Reid , Johnson Andrew
Published: October 2023

Fracture monitoring and diagnosis by fiber optic sensing technology provides invaluable information about stimulation efficiency. This technology becomes more critical for multistage fracturing over long horizontal wells. The combined analysis of distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) measurements has been used to map the fluid distribution during hydraulic fracturing, and fracture volume at the cluster level and at the stage level can be estimated from the analysis. In this paper, based on the interpretation of models for DTS and DAS, we extend the application to fluid containment and stage isolation evaluation.

In plug and perf hydraulic fracturing, when a stage is finished pumping, the stage is isolated by a plug, and the next stage is perforated then fractured. If the plug is not functioning correctly, fracture fluid enters the previous stage, causing an uneven fluid distribution, and possibly more severe perforation erosion. Both DAS and DTS monitoring can record this phenomenon when it happens. Interpretation models are built to quantify the fluid distribution with the effect of plug leakage included. From DTS measurements, cooling below the stage being completed is counted as the fluid from the current stage. Given this information, the reservoir thermal model can estimate the volume of leakage. From the DAS measurement, we first interpret the volume distribution based on frequency band energy level to compare with the DTS interpretation, we then use the volume to estimate perforation erosion. Perforation erosion measurements from a downhole camera are used to confirm the estimation. With this approach, we understand the fluid distribution, plug performance, and the importance of stage isolation on perforation erosion during a multistage fracture treatment. The information can then be used to analyze and optimize completion and fracture treatment design.

Field examples are presented in the paper to support the discussion, findings, and conclusions. Based on the results of fluid distribution estimated, we observed that higher injection rate and larger fluid volumes may create more uniformly distributed fluid. When considering communication between stages, the DTS and downhole camera show that there is a correlation between fluid distribution and perforation eroded area. In the completion design, only limited parameters show strong impact on fluid distribution and perforation erosion.
Successful Application of Intelligent Completions in a Deepwater Gulf of Mexico Water Injector
Authors: Bolingbroke H. F. , Saripally I. , Webb K. , Gandhi N. , Askeroglu I. , Beecher R.
Published: October 2023

In complex reservoirs with challenging operating conditions, intelligent completions have proven to be instrumental in optimizing water injection and conducting reservoir surveillance. In this paper, we present a multi-disciplinary case study from deepwater Gulf of Mexico (GOM) highlighting the critical role played by an intelligent completion in a dual zone water injector.

The GOM field in this study is a Pliocene-aged, high-density turbidite sand consisting of multiple stacked reservoirs. It is a mature field with more than 15 years of production and water injection. The hybrid wells are tied back to the offshore platform via individual marine risers, so well-bay slot availability is limited. Thus, a dual zone injector with downhole choking was planned to maximize wellbore/slot utility. The intelligent completion provided the ability to inject selectively at desired rates into each zone for waterflood optimization.

This case study demonstrates an integrated framework of planning, drilling, completing, and operating a state-of-the-art intelligent well in an offshore environment, including:

Wellbore planning: A dual-zone injector was chosen to make the best use of existing infrastructure and slot availability. Un-swept and pressure-depleted reservoir targets were identified through seismic and pressure data. Numerical models were built to aid with downhole choke design and to forecast the response seen in offset producers. Drilling and Completions: Factors such as wellbore availability, directional constraints, and collision avoidance were reviewed. Wellbore component selection included an intelligent completion with downhole choking and a triple downhole pressure/temperature gauge. Metallurgy specifications, jewelry positioning, perforation strategy, and frac design were considered. Operations: The ability to isolate either of the two completed zones allowed for high-confidence surveillance and waterflood optimization. Additionally, the intelligent completion greatly assisted with acidizing and adding waterflood tracers, as each zone could be treated or isolated individually.
Laboratory Measurements of Permeability and Porosity of the Matrix and Created Fractures: Application to the Pressure Falloff Analysis Following Well Stimulation to Determine Effective Fracture Spacing in Field
Authors: Mindygaliyeva B. , Uzun O. , Amini K. , Kazemi H.
Published: October 2023

We present an analysis of several multi-rate pressure falloff data following well stimulation in the Utah FORGE enhanced geothermal system (EGS) injection well. The purpose of the analysis was to determine the effective stimulated permeability and representative fracture spacing in the stimulated formation volume. The Utah FORGE geothermal system is a very low-permeability, dry granitoid; therefore, it is necessary to create permeable flow channels in the formation for the injection water to penetrate and extract heat for power generation. We have previously used the same pressure falloff analysis procedure in numerous unconventional reservoirs. We measured the permeability of the matrix rock and the permeability of an embedded fracture, as well as the porosity for several 1-1/2-inch by 2-inch cores. Then, we used the measured permeabilities and porosities in the analysis of multi-rate pressure falloff field data to determine the effective macro-fracture spacings adjacent to the hydraulic fractures. The cores used for the experimental study were outcrop granite, geothermal granitoid, and several unconventional (Niobrara, Codell, Wolfcamp) reservoirs. To determine a representative macro-fracture spacing associated with the hydraulic fractures, the pressure falloff field data analyses were fine-tuned via numerical modeling iteratively. Finally, the experimentally measured core porosities and permeabilities were used as input data for the interpretation of the analytical model used in the pressure falloff test analyses. Such analysis indicates that fracturing fluid entering the rock surrounding the hydraulic fracture is dominated by the micro-fractures. Nonetheless, it is important to note that FORGE rock is highly water wet; thus, water imbibition plays a significant role in water entering the rock pores despite their low permeabilities. Finally, one can appreciate the importance of the stimulated fractured zone both in providing surface area for heat extraction in geothermal wells and for mass transport in improving primary production and EOR in unconventional shale reservoirs.