bluuebunny/crossref_metadata_2025 huggingface dataset:
Segmentation of X-Ray Images of Rocks Using Deep Learning
Authors: Ar Rushood Ibrahim , Alqahtani Naif , Wang Ying Da , Shabaninejad Mehdi , Armstrong Ryan , Mostaghimi Peyman
Published: October 2020

Segmentation of X-ray images of rocks is an important step in digital rock technology. Current segmentation methods often suffer from operator bias and can be time-consuming. To overcome these limitations, an automated image segmentation model is created for pore scale images through the use of convolutional neural networks. A dataset of micro-Computed Tomography (CT) images of sandstones is considered. To create the ground truth data for training, Scanning Electron Microscopy 2D and micro-CT 3D images are used to obtain accurate segmentation masks. Three models are trained with the available data: One with limited images, one with the full dataset, and one with augmented data. The data augmentation is achieved by increasing sample size through image partitioning. The data set for each model is divided into training, validation, and testing with a 60/30/10 split, respectively. The U-Net architecture, designed to work with limited training data, is used to develop the models. Further validation of the models is performed on a different dataset unseen by the models. The Minkowski functionals and permeability of the volume generated by the segmented images are computed and compared with the ground truth segmentation. Against the unseen dataset, the models scored a dice coefficient of 0.9479, 0.9518, and 0.9599, respectively. We discuss the potential for improvement by data augmentation and fine-tuning. One limitation of the models is with the deficiency of variety in training data as both SEM and micro-CT is required to obtain the segmentation masks. We also discuss the performance of the model on unseen samples and show the potential improving efficiency in the digital rock technology. The models provide a quick and accurate segmentation for images of sandstones without the influence of operator bias, and the method shows promise for further development and improvement.
Integrated Approach for Well Interference Diagnosis Considering Complex Fracture Networks Combining Pressure and Rate Transient Analysis
Authors: Qin Jiazheng , Cheng Shiqing , Zhu Jing , He Youwei , Yu Wei , Rui Zhenhua , Sepehrnoori Kamy
Published: October 2020

Well interference has been historically investigated by pressure transient analysis, while it has shown that rate transient analysis has great potential in well interference diagnosis. However, the impact of complex fracture networks (CFN) on rate transient behavior of parent well and child well in unconventional reservoirs is still not clear. To further investigate, this paper develops an integrated approach combining pressure and rate transient analysis for well interference diagnosis considering CFN.

To perform multi-well simulation considering CFN, non-intrusive embedded discrete fracture model approach was applied for coupling fracture with reservoir models. The impact of CFN including natural fractures and frac-hits on pressure and rate transient behavior in multi-well system was investigated. Obvious distinctions could be viewed for different kinds of CFN on diagnostic plots compared with single-well model. Due to the interference from surrounding producers, new flow regimes including compound linear flow and interference flow would occur on loglog plot. In general, the effect of natural fractures seems to be more evident than that of frac-hits. Blasingame plots could be categorized into different types based on various CFN patterns.

Application of this integrated approach to demonstrates that it works well to characterize the well interference among different multi-fractured horizontal wells in a well pad. Better reservoir evaluation can be acquired based on the new features observed in the novel model, demonstrating the practicability of the proposed approach. The combination of pressure and rate transient analysis can reduce the uncertainty and improve the accuracy of the well interference interpretation based on both field pressure and rate data.
Acoustic Data Driven Application of Principal Component Multivariate Regression Analysis in the Development of Unconfined Compressive Strength Prediction Models for Shale Gas Reservoirs
Authors: Iferobia Cajetan Chimezie , Ahmad Maqsood , Salim Ahmed Mohammed , Sambo Chico , Michaels Ifechukwu Harrison
Published: October 2020

Unconfined compressive strength (UCS) equally represented as geomechanical strength remains a critical mechanical property in the successful implementation of key technologies for shale gas reservoirs’ development and production. Attention has been less concentrated on prediction models’ development for shale geomechanical strength evaluation. Majority of the existing shale geomechanical strength correlations are dependent on single log input parameter, which is insufficient to account for the complex and non-linear behaviour of UCS across the entire reservoir interval of interest. The high relevance of UCS has therefore triggered the need for the application of an integrated system of principal component – multivariate regression analysis in driving UCS predictive models’ development for shale gas reservoirs. Generated acoustic datasets of notable shale gas reservoirs (Marcellus, Montney, Longmaxi and Roseneath) in respective countries (United States of America (USA), Canada, China and Australia) were used. Statistical test analysis was conducted in validation for wider applications of the developed UCS prediction models.

Models development were driven by 21,708 datapoints of acoustic parameters, models’ accuracy ratings were above 99%, R-squared values had high degrees of closeness to unity, mean absolute percentage error (MAPE) values were at less than 10% and coefficient of variation (COV) at less than (1.0). UCS prediction models were all dependent on multiple direct log measured acoustic parameters in distinction to existing UCS empirical correlations; thus, a pure reflection of significant boost to the accuracy and reliability of UCS measurements for shale gas reservoirs. The developed prediction models will promote geomechanical strength accountability and lead to creation of a robust base in minimization of wellbore instability problems, optimization of wellbore trajectory and containment of hydraulic fractures. This will significantly contribute in putting gas resources of shale reservoirs with enormous potentials, at the forefront of quantitatively meeting natural gas requirements in global energy demand.
Quantifying Fracture Interference and Allocating Load Recovery and Hydrocarbon Production in Various Well Configuration Using Chemical Tracers
Authors: Tian Wei , Darnley Alex , Dempsey Chris
Published: October 2020

This paper presents a method of using chemical tracer data to quantitatively evaluate interwell communication in various well configurations by combining raw tracer data with field production data. Qualitatively, tracer breakthrough in an offset well indicates that there is communication between the infill and primary well, but by utilizing the method described in this paper, the fracture driven interaction (FDI) severity can be quantified by determining the total mass of tracer produced out of the primary well and new wells. The technique yields an allocation of load fluid and hydrocarbon recovery at each well and associated formation.
Sensor Fusion and Machine Learning Techniques to Improve Water Cut Measurements Accuracy In Multiphase Application
Authors: Barbariol Tommaso , Feltresi Enrico , Susto Gian Antonio , Tescaro Diego , Galvanin Silvia
Published: October 2020

Objectives/Scope

A Multi-Phase Flow Meter (MPFM) performs Water Liquid Ratio (WLR) estimations using a dedicated sensor relying on one physical principle (e.g. electrical impedance). The accuracy of the WLR sensor might also be dependent on the flow properties. An approach based on Machine Learning techniques and multi-sensors data fusion has been implemented to enhance the reliability and accuracy of the WLR estimations in Multi Phase application using onboard sensor measurements of a MPFM.

Methods, Procedures, Process

In order to improve the estimations of multi-phase applications, we exploit the availability of historical data collected with heterogeneous sensors; the underlying idea of the proposed approach is to exploit such data with Machine Learning supervised techniques to provide accurate measures. In this work we compare modern supervised learning approaches like Random Forest, Gradient Boosting techniques and Kernel methods. The proposed methods have a relatively simple form that can be deployed also in embedded applications.

Results, Observations, Conclusions

In this work, we will show through extensive experiments that the proposed approach could improve the original estimations. The algorithms underlying the proposed approach have been trained using data collected at flow loops test facilities with different flow conditions. The best model has been chosen not only for its predictive performances, but also looking at the computational time needed to make a prediction and considering its robustness to outliers. As expected, depending on the dataset numerosity, the best performing model can change: we provide experimental results for various dataset sizes in order to help practitioners choose the best regression method depending on the available data numerosity. An additional considered aspect is the computational time of the various approaches, which may be a relevant characteristic to be evaluated before rolling out productive solutions.

Novel/Additive Information

To increase the accuracy of MPFM, a sensor fusion technique that benefits from the many measurements collected by the MPFM, has been developed. Many different models have been compared on: prediction performances, confidence interval, robustness to outliers, execution time. The resulting model provides enhanced estimations equipped with confidence intervals that can be used for prediction quality assessment and associated risk management.
Can Paraffin Wax Deposit Above Wax Appearance Temperature? A Detailed Experimental Study
Authors: Aguiar Janaina I. , Nerris Anthony A. , Mahmoudkhani Amir
Published: October 2020

Shale producers in North America continue to face challenges with paraffin wax deposition in well bores, production tubing and flowlines as production declines and artificial lift methods such as gas lift are applied. Preventative measures are often based on traditional screening and assessment methods which rely on crude’s wax appearance temperature (WAT). Recent studies have shown that operators are increasingly turning to costly remediation program and stimulation jobs to maintain production rates as oil wells decline at faster rates than anticipated. It appears in many cases that these declines can be exacerbated by downhole organic fouling and wax deposition that surprisingly may have occurred above the original WAT. This paper aims to conduct a root cause analysis to identify the key internal and external factors impacting an oil’s WAT. Four crude oils and field wax deposits from Gulf of Mexico, South Texas and West Texas areas were used for this study. Due to the unique composition of the field deposits and depleted crude sample available for analysis, a novel strategy for lab screening was adopted. Crude oil samples were examined "as received" and after reconditioning via the addition of solvents and/or field deposits. Further measurements were performed to identify and quantify the effects of the addition of production chemicals particularly hydrate inhibitors. A series of dispersion and deposition tests were then conducted in order to demonstrate the potential impacts of incompatible chemistries. Fractionation based on solubility revealed a dynamic behavior for the WAT of crudes that corelated to their paraffin content and distribution. Samples containing C45+ paraffin chains demonstrated significant WAT changes upon reconditioning. The addition of methanol and MEG typically used as hydrate inhibitors, impacted the WATs of the crudes as measured by DSC showing increases in the WATs compared to unconditioned samples. An additional suite of dispersion and deposition testing conducted on the same samples supported the findings of the DSC studies. A nonlinear correlation was found between increasing WAT and paraffin deposition rate. The approach outlined in this paper provides a more accurate field condition simulation leading to more effective inhibitor selection and ultimately improved flow assurance management in more complex production systems. The methodology of mimicking hydrocarbon fluid behavior was the key factor identified by the root cause analysis and correlated to the series of past failures attributed to organic fouling. WAT was found to be a parameter that can vary for a crude oil over the life of a production system. With the current evolution of shale oil production in North America and around the world, we expect these findings will also be relevant to unconventional production and will aid the oil industry to anticipate and manage previously unforeseen problematic paraffins in production systems.
Automated Gas Lift System Optimization Through Combined Data Analytics and Wellbore Modeling Approach: A Case Study in an Offshore Middle East Oilfield
Authors: Surendra Meher , Deng Lichi , Kansao Rami , Davani Ehsan , Darabi Hamed , Castineira David
Published: October 2020

Systematic and comprehensive analysis of gas lift operations must include historical performance evaluation and heuristic diagnostics for identification of suboptimal performers. Reliable nodal analysis models are necessary to optimize the gas lift systems. Though some degree of automation is currently possible, this process still takes substantial effort and time. The work presented here is a streamlined, repeatable, and automated workflow to diagnose and optimize gas lift operation through analytics, reliable wellbore modeling and calibration that reduces the time from days to hours. The workflow is also very easily repeatable, which makes it very efficient to update when new data is available.

The workflow combines the emerging data analytics efforts in the oil and gas industry along with traditional gas lift optimization guidelines to identify artificial lift-related key recovery obstacles and corresponding development plans. This novel combined approach proves the effectiveness and necessity of augmented artificial intelligence, and the case study of field analysis and execution further endorse the impact of such optimization workflow for gas lift assessment and operations. It builds from data-driven and engineering-based workflows that compute smart metrics and dashboards based on the historical well production and the gas lift systems performance. Several KPIs and metrics are utilized, some of which are industry standard while others are intuitively built exclusively for this workflow.

In this paper, we present the results and challenges in applying this workflow to an offshore Middle East oilfield, with over 50 gas lift wells. As always with field data, several aspects of the data had to be addressed. Accuracy and relevancy of data was questionable. We developed several workflows to address the missing/incorrect data to ensure the robustness and credibility of the results from the workflow. Due to the practical implication of the analysis, stringent quality control and error margins were maintained throughout the analysis. No nodal analysis models were available, consequently models were built and calibrated as a part of this effort. Overall field and facility constraints were also incorporated to ensure results were achievable in the field.

The optimized operational plan would yield an additional 15 to 20% gains over current production rate. Further benefits by upgrading the gas lift design are also quantified using the proposed workflow. The time required to construct, calibrate, and optimize around 50 wells was less than two weeks.
Novel Class of Zinc-Free Heavy Clear Brines for HPLT Applications
Authors: Liimatta Eric , Lambeth Gregory , Liu Yunqi , Messler David
Published: October 2020

In an effort to increase oil production over the past twenty years, the oil industry has moved into deep water for new field developments. During this time, progressively deeper wells containing geopressured reservoirs require the use of high density completion brines. Many of these reservoirs require the use of completion brines above 14.7 ppg. Historically, zinc bromide solutions have been used to provide the required density and true crystallization temperature (TCT) for these reservoirs. However, health, safety, and environmental concerns around zinc bromide have caused operators to seek alternative solutions.

The oil and gas industry uses a large amount of heavy brines in the completion of high pressure-low temperature (HPLT) wells, and there are currently very limited options for high density (>14.7 ppg), low TCT fluids that do not contain zinc. One option, cesium formate, is prohibitively expensive, and the other, based on existing halide technology, has a lower density limitation than this new class of clear brine fluid.

This paper describes a novel, zinc-free, high-density, low true crystallization temperature brine fluid developed by Albemarle Corporation. We will discuss the testing performed to characterize this new fluid. This new class of brine fluid fills a gap in fluids technology for a fluid suitable for high pressure, low temperature applications at higher densities than previously available. Further, this is accomplished in an environmentally friendly heavy brine fluid that contains no Environmental Protection Agency (EPA) listed materials.
Making Digital Collaboration More Efficient and Reliable With Second Generation Standard Interoperability Protocol
Authors: Neri Philip , Philo Ross
Published: October 2020

The rapid pace of digitalization of E&P operations is generating a sharp increase in the volume of data being exchanged between different disciplines, departments, partners and vendors. To facilitate the exchange of data across these many entities rapidly and in a uniform manner and with no loss of information, the ETP (Energistics Transfer Protocol) WebSocket-based two-way protocol, originally introduced in 2014 and updated in 2016 (McKenzie 2016) to support streaming of real-time data from drilling rigs to onshore monitors, has been expanded.

The standard ETP data streaming protocol delivers a near-instant streaming of data from rig to onshore centers with the additional ability to entertain multiple connections to perform the streaming to several recipients concurrently. Modes were also present in that version to make use of the protocol for direct application interoperability. However, the latter were not fully developed and as a result saw limited uptake after the publication of the standard. The new version of the protocol aimed at improving the real-time data streaming capabilities based on the experience accrued over 3 years of deployment, as well as completing the interoperability features and adding new sub-protocols to support the interrogation and selective retrieval of data from a server as well as other actions that facilitate direct application interoperability. A data system or application can be set to signal to listening systems instances of a new object or changes to existing objects. Each interoperability connection is initiated by an application acting as a client and connecting to an application that is an active server at that time. Once the connection is in place, the duplex or bi-directional nature of the protocol stack makes it possible for either application to make requests to the other one.

These application interoperability capabilities offer an alternative to the existing data transfer process that uses files as a mechanism to move data from one application to another. The file-based process remains relevant for transmittals that require the creation of a data package that can be loaded into systems not connected to the same network, as well as for archival purposes.
The Effects of Geomechanics, Diffusion and Phase Behavior for Huff-n-Puff IOR in Shale Oil Reservoirs
Authors: Zheng Shuang , Sharma Mukul
Published: October 2020

Lab experiments and numerical modeling have indicated that gas injection for IOR in tight oil reservoirs is technically feasible. Several operators have conducted pilots in the Eagleford and Bakken shales for a huff-n-puff IOR strategy with mixed results. Our objective in this work is to study the impact of (a) geomechanical effects during injection and fracture closure during production, (b) injection rate effect during huff-n-puff processes, (c) timing effect in huff-n-puff process, (d) phase behavior effects for huff-n-puff oil recovery, and (e) impact of soak time on oil recovery.

We developed and utilized a fully coupled geomechanical compositional fracturing/reservoir simulator for gas injection in tight oil reservoirs. The model calculates stress changes due to both poroelastic (pressure changes) and mechanical (fracture opening and closing) effects. Permeability hysteresis during loading/unloading cycles is also considered. The simulation procedure involves the following steps: (a) The well is produced for a period of time (b) Gas is injected into the well and this is simulated by specifying the injection rate and gas composition (c) The well is produced again after some soaking period, and the results are checked for any improvement in the oil recovery.

Based on our simulation studies, we observed several important trends. The degradation of permeability over multiple loading/unloading cycles due to hysteresis together with the poro-elastic effect severely impacts the oil recovery in later cycles. It was found that incremental oil recovery decreases after several huff-n-puff cycles. It was found that if higher gas injection rate gives higher oil recovery, but the oil recovery does not increase linearly with the injection rate. Phase behavior is found to be a key factor in the oil recovery and rich gas injection gives the best results. The impact of timing to initiate the huff-n-puff IOR was also studied. The soak time increases the ultimate oil recovery, but its impact is not significant in the study.

Our simulation results provide operators with significant new insights on the design of huff-n-puff IOR. It is shown that fracture widening and closure during huff-n-puff cycles have a significant impact on oil recovery. The novelty of the work is the development and use of compositional geomechanical model for IOR performance evaluation.
Production Rate Measurement Optimization using Test Separator and In-Well Sound Speed
Authors: Ünalmis ö. Haldun
Published: October 2020

The litmus test for downhole multiphase flowmeters is to compare the measured phase flow rates with the test-separator rates. In most cases, the composition of the measurand is required for flowmeters and is typically obtained from bottomhole fluid samples. Extracting and analyzing fluid samples is an expensive process mostly done at the initial stages of field development. Because the composition is not always available and is usually old, flowmeters may have subpar performances when compared to test separators. In this work, it is shown that once the test-separator data are available, measuring mixture sound speed downhole will ensure the optimization of a multiphase flowmeter system without needing to obtain new fluid samples. This novel method is demonstrated in a North Sea case history.

This method of optimizing flow rates is independent of the measurement device because the required flow velocity and sound speed measurements could be obtained from separate and generic devices. For example, the fluid bulk velocity and mixture sound speed could be measured by a point measurement device and a distributed acoustic sensing (DAS) system, respectively. The main challenge in a flow-velocity/sound-speed measurement system is to determine individual phase sound speeds so that the mixture phase fraction could be correctly modeled using Wood's mixture sound speed model. The phase fraction from the separator tests could be used as the target value to optimize the performance of the system. This is done with a backward calculation of the sound speed of individual phases. Pressure and temperature variations at measurement locations as well as the pipe compliance effects are also accounted for in this approach. Following the adjustment of individual phase sound speeds, a forward calculation using the same model yields a phase fraction close to the actual value, which could be improved further by an iterative approach.

A downhole optical flowmeter in a North Sea field measured mixture velocity and sound speed. Well test results indicated that the water cut was underreported and phase flow rates did not match the test-separator rates. Instead of halting production and going through a fluid sample analysis cycle, the test-separator water cut was used as the target value to optimize oil phase sound speed using Wood's model with a backward calculation. The difference in oil sound speeds was extrapolated to other pressure and temperature conditions, and forward calculation showed that separator tests and flowmeter measurements closely matched. Subsequent flowmeter and test-separator data confirmed excellent agreement.

Using well test data and sound speed to optimize phase flow rates is a novel method that has not been previously demonstrated. This method is independent of device type, broadly applicable, and furthers the understanding of multiphase flow measurement.
Design for Reliability: Purpose Driven Sand Control Methods for Cased and Perforated Wells
Authors: Soroush Mohammad , Roostaei Morteza , Mohammadtabar Mohammad , Hosseini Seyed Abolhassan , Mahmoudi Mahdi , Sadrzadeh Mohtada , Ghalambor Ali , Fattahpour Vahidoddin
Published: October 2020

The historical challenges and high failure rate of using standalone screen in cased and perforated wellbores pushed several operators to consider cased hole gravel packing or frac-packing as the completion of the choice. Despite the reliability of these options, they are more expensive than standalone screen completion. Since several developments are not designed for cased hole gravel pack or frac-pack, purpose-driven sand control methods for cased and perforated wells are recommended.

This paper employs a combined physical lab testing and Computational Fluid Dynamics (CFD) for lab scale and field scale to assess the potential use of the standalone screen in completing the cased and perforated wells. The aim is to design a fit-to-purpose sand control method in cased and perforated wells and provide guidelines in perforation strategy and investigate screen and perforation characteristics. More specifically, the simultaneous effect of screen and perforation parameters, near wellbore conditions on pressure distribution and pressure drop are investigated in detail.

A common mistake in completion operation is to separately focus on the design of the screen based on the reservoir sand print and design of the perforation. If sand control deemed to be required, the perforation strategy and design must go hand in hand with sand control design. Several experiments and simulation models were designed to better understand the role of perforation density, the fill-up of annular gap between the casing and screen, perforation collapse and screen plugging on pressure drop. The experiments consisted of a series of step rate tests to investigate the role of fluid rate on pressure drop and sand production. There is a critical rate in which the sand filled annular gap will fluidize and also sanding would be different for different fluid density. Both test results and CFD simulation scenarios comparatively allow to establish the relation between wellbore pressure drop with screen and perforation parameters and determine the optimized design.

The results of this study highlight the workflow to optimize the standalone screen design for the application in cased and perforated completion. The proper design of standalone screen and perforation parameters allows maintaining cost-effective well productivity. Results of this work could be used for choosing the proper sand control and perforation strategy, rather than using gravel packing and frac-packing methods in cased and perforated completions.
Redefining Technical Limit Managed Pressure Directional Drilling Solution in Depleted South Texas Lessons & Best Practices From 5 Wells
Authors: Oliver John , Ngan Alex , Arnone Maurizio , Valecillos Juan , Stich Chad
Published: October 2020

This paper will discuss the Managed Pressure Directional Drilling fit-for-purpose solution deployed to meet the drilling challenges faced in 5 consecutive wells drilled in South Texas, USA. This innovative solution integrates a state-of-art Rotary Steerable System (RSS) with Managed Pressure Drilling (MPD) technology. Drilling hazards such as well control events, simultaneous kick-loss, and stuck pipe were mitigated, and an improved drilling performance with a reduction of NPT as compared to other directional drilling systems.

The solution requires the integration of two highly technical disciplines, MPD and Directional Drilling. Hence, a Joint Operating & Reporting Procedure (JORP) and a defined communication protocol are crucial for effective execution. The solution is based on a rigorous Drilling Engineering process, including detailed offset wells analysis to deliver a comprehensive risk assessment & mitigation plan in collaboration with the Operator to tackle drilling hazards without compromising the directional drilling requirements.

This paper will summarize the 5 wells operations, the drilling optimization results, and the lessons learned from an integrated services point of view in terms of deliverables that made the difference on this project and allowed the Operator to achieve their objectives. In particular, the effective communication protocol between the directional drilling services, MPD services, and rig contractors to ensure safe operational alignment.
RFID Control Valve Leading to Digitalization of Plant
Authors: Khan A.
Published: October 2020

A radio frequency identification (RFID) tag can be used to identify and track objects wirelessly through electromagnetic fields. Application in today's markets include logistics and goods tracking. An innovative way to use RFID could be integration with control valves at plants, leading toward digitalization of the plant and IR4.0.

RFID enabled control valves, integrated with IR4.0, can give a holistic view of control valves across the plant. In this case, an RFID tag could be attached to a Smart Control Valve Head, acting as a controller and actuator. Any alarm or malfunction could be reported through the Smart Control Valve Head to a central control system. A web-based solution could be added in layers, which enables the notification to of appropriate workgroups. It can also enable improved preventive maintenance.

The solution will be based on a wireless identification and sensing platform (WISP), which will use the concept of RF Energy Harvesting using RFID with a rectenna — a combination of antenna and rectifier. An antenna is used to collect ambient RF energy, which is available around us in the form of electromagnetic waves from mobile phones and wireless networks. A rectifier converts the RF energy into electricity for powering up RFID, thereby offering a wireless and battery-less RFID solution. A RFID tag connected to the Smart Control Valve Head will form a localized control loop with wireless communication to the central control system for data sharing and smart analytics.

The proposed concept of RF energy harvesting using a rectenna with an RFID-enabled control valve can lead toward the possibility of a decentralized wirelessly controlled valve, digitalization of plants with superior maintenance, and a new paradigm of IR4.0.
Assurance of the Asset Action Plan: A Strategic Endeavor Toward a Credible and Reliable Forecast
Authors: Al-Ghnemi Mohammad , Kumar Ashish , Mendjoge Ashish , Bora Anup , Chandan Thakuria , Al-Najdi Ali , Al-Bahar Mohammad
Published: October 2020

Oil companies are facing several challenges from external and internal environment like volatility of crude oil price, capex reduction, subsurface uncertainty, delay in the surface facilities etc. that impacts the long-term strategic plans. Kuwait Oil Company (KOC)'s annual Asset Action Plan (AAP) operationalizes the long-term strategy of the company assurance of annual AAP is key for having a credible forecast and meeting long term goals. A robust Corporate Assurance process has been developed that consists of workflows that will guarantee company's ability to develop and execute credible field development plans. A review on proper planning, execution and alignment of different business processes is required during assurance of Asset Action Plan. This assurance process provides confidence to the management in approving the AAP.

Opportunity based Asset Action Plan (AAP) process is the backbone of KOC's annual business planning and portfolio management system. This allows alternative portfolio choices and management can make the right decision. The opportunity will provide consistency and clarity of the Portfolio constituents and common rational basis for investment decision making and allow for alignment between the KOC major business processes.

AAP process is carried out annually and is initiated through high level business guidelines management. During finalization of AAP, an assurance review by corporate technical team for large national companies having multiple assets is considered as best practices that support management in approving the AAP and to steer the company in right direction.

AAP Assurance process involves reviewing the forecast with the historical performance of the reservoir, planned activities, expected outcomes from the activities, feasibility and associated cost. A systematic three stage process has been adopted to conduct AAP Assurance for reservoirs which are at different phases of development.

This assurance workflow and methodology helps to align changing oil and gas scenarios, different business process, health of the reservoirs and meeting future production targets.

This process ensures that proposed AAP plan will be able to deliver production target commitments and identify any gaps and propose mitigation plans. This also confirms that ongoing development plans are in alignment with facility planning. It also validates conformance of the adopted reservoir development and management workflows with global best practices (analogue reservoirs) to maximize recovery and maintaining health of reservoir.
Fruit Extracts as Natural, Green, Non-Toxic Corrosion Inhibitors
Authors: Ng Jun Hong , Almubarak Tariq , Nasr-El-Din Hisham A.
Published: October 2020

Corrosion inhibitors currently used in the oil and gas industry are associated with environmental concerns and severe health risks. Recent advancements in corrosion inhibition technology had successfully tackled environmental concerns, but still faces issues with toxicity and performance at high temperatures. This work aims to develop environmentally friendly and non-toxic corrosion inhibitors that can overcome these limitations. Extracts of 14 common fruits were tested as sources of potential corrosion inhibitors.

In order to determine the inhibition effectiveness of the different fruits, N-80 coupons were exposed to 15 wt.% HCl solutions at temperatures between 77-250 °F with 0.2-2 wt.% of dried ground fruit for 6 hours. In addition, a control solution containing no corrosion inhibitor was used to establish a corrosion rate for a base case. Upon identifying high performing dried ground fruits, extracts of these fruits were subsequently tested to save cost by minimizing quantity needed while achieving acceptable performance.

At a concentration of 2 wt.%, fruits 1 and 2 were found to perform the best, exhibiting more than 98% corrosion inhibition efficiency at 77°F. Fruits 11 and 12 were observed to perform the worst, going so far as to enhance corrosion on the coupons. At 150°F, the corrosion rate of fruit extract 1 was 0.00436 lb/ft2, while that of fruit extract 2 was 0.0277 lb/ft2. At 200°F, the addition of a corrosion inhibitor intensifier resulted in a corrosion rate of 0.00130 lb/ft2 for fruit extract 1 and 0.0173 lb/ft2 for fruit extract 2. At 250°F, a second corrosion inhibitor intensifier was used. The resulting corrosion rate was 0.0320 lb/ft2 for fruit extract 1 and 0.00963 lb/ft2 for fruit extract 2. These results show that a naturally occurring, green, non-toxic corrosion inhibitor can be developed from these fruits and can comfortably pass the industry requirement of achieving corrosion rates below 0.05 lb/ft2 for low carbon steel tubulars.

Corrosion during acid treatments causes destruction to the tubulars and downhole equipment. Consequently, this leads to an increase in expenditure to maintain well production rates and well integrity. Therefore, corrosion inhibitors must be included in any acid treatment formulation. The results in this work share two new naturally occurring, green, non-toxic, high-temperature stable corrosion inhibitors that can be developed from fruits and can successfully protect the tubular during acid treatments.
Phase Behavior Modeling of Acid-Gas Aqueous Systems CO2, H2S, CH4, Water and In-Situ pH Measurements in Applications to Wellbore Integrity and Top-of-Line Corrosion
Authors: Dindoruk Birol , Ratnakar Ram R. , Suchismita Sanyal
Published: October 2020

We present thermodynamic modeling and pH measurements of fluid systems containing acid-gases (e.g. CO2 and H2S), water and hydrocarbons – replicating the production and shutdown conditions in sour fields – for the purpose of evaluating top-of-line corrosion and wellbore integrity, and screening/selection of the proper wellbore materials. In particular:

An EOS model using Peng-Robinson EOS in combination with Huron-Vidal mixing rule for aqueous sub-system is developed. In the model, subject EOS parameters are calibrated against existing thermodynamic data (saturation data for pure components and solubility data for binary systems) in literature. A new in-situ pH measurement data is presented for a model system corresponding to sour field. It was found that the wellbore can be subjected to pH levels as low as 2.7 with reservoir fluid containing 12 mol% CO2 and 88 mol% methane with downhole flowing conditions of 200 bar and 150°C, and wellhead shut-in conditions of 300 bar and 4°C, as observed from the experiments. A modeling workflow is developed to estimate pH of the condensed water as a function of temperature and composition of the aqueous phase. The comparison between prediction and experimental measurement show very good match between the two (within pH ±0.1).

Such studies (pH measurements and prediction) are not available in literature but play important role in material screening and assuring wellbore integrity for sour fields. More importantly, sensitivity analysis can be performed to investigate the effects of various factors (such as reservoir temperature/pressure, shutdown conditions, and compositions or extent of souring) on pH prediction. Furthermore, the methodologies developed through this work can also be extended to reservoir facilities, pipelines, sour gas disposal/handling units, as well as, downstream systems such as as water-utilities, reactor plants and refineries. The work can also support for regulation/licensing for these sour systems.
The Effect of Margin and Reserves/Production Ratio on Oil and Gas Transaction Multiples
Authors: Gajdica Ronald , Byrne Randall
Published: October 2020

Precedent transaction multiples are often used to estimate the market value of oil and gas assets. The multiples typically used for valuation include production, reserves, and cash flow multiples. Improper application of these multiples can lead to valuation estimates that are significantly different than actual market value. This paper outlines a method to improve the accuracy of market value estimates from multiples analysis by incorporating (1) the correlation between multiples and proved reserves to production ("R/P") ratio, and (2) the effect of profit margin ("margin") on transaction multiples. The effect of margin is especially relevant because some transaction metrics are not necessarily valid in the current market due to significant changes in commodity prices.

Economic runs for a variety of conditions were made to observe the theoretical effect of R/P ratio, margin, and discount rate on net present value. The net present value at a 10% discount factor ("PV10") was used as a proxy for market value. Then, production, reserves, and cash flow multiples were calculated and analyzed. Relationships between the different variables were studied, and equations to calculate the various multiples as a function of R/P, margin, and discount rate were constructed. Comparison of multiples generated from discounted cash flow ("DCF") regression analysis to actual transaction data show that the shapes of the various curves generated agree with the historical trends.

This paper also includes commentary on how to correctly apply the multiples to asset valuation, equations to calculate the various multiples, and a discussion of pitfalls to avoid when performing multiples analysis.
Successful Installation of a Down-Hole Fiber Optic Wetmate Connection System
Authors: Samuelson Marc , Harris Shane , Schrader Kirby , Mendez Luis
Published: October 2020

In July and again in September 2019, six-fiber downhole fiber optic wet-mate connections were successfully landed on fiber enabled lower completions, "lighting up" the completion from the wellhead to the reservoir. The tools that enable this technology must simultaneously align six fibers the diameter of a human hair end-to-end in a downhole environment.

These deployments are the first successful installations of fiber optic downhole wet connects in the North Sea and it represents a step change in the information that can be obtained from permanently installed sensors at the reservoir in a multi-trip completion. To date, opportunities for fiber optic sensing have been quite limited in multi-trip completion systems. This has restricted the use of many fiber optic technologies to the upper completion rather than where it can provide the most impactful data - at the reservoir.

This paper will present a brief history of the development and validation of this fiber optic connector system design including specific qualification testing for these North Sea wells. The fiber optic downhole wet-mate connector is a result of more than a decade of engineering design, testing and qualification. Further refinements were made with this specific group of wells in mind, and the system was optimized, assessed and tested with support from the operator. A close working relationship between the operator and the service company enabled optimization of the tools as well as the entire completion to reduce the risk of NPT and infant mortality of the equipment.

The operations resulted in a successful connection of all six fibers and a fiber optic instrumented lower completion with full well surveillance capability. Six individual fibers were connected simultaneously, enabling sensing of distributed temperature, distributed acoustics, and two pressure/temperature gauges on the exterior of the lower completion with direct contact to the reservoir. Optical losses across the connector were less than 0.5 dB for all fibers.

This fiber enabled completion allows the completions and reservoir engineers to gather and interpret the distributed data that obtained by the interrogators from the interaction of the optical fiber and its surrounding environment.
Large Scale Subsurface and Surface Integrated Asset Modeling - Lessons Learned
Authors: Hafez Hafez , Saputelli Luigi , Mata Carlos , Mogensen Kristian , Di Sarria Andrea , Singh Nicholas , Mohan Richard , Escorcia Alvaro , Pires Joshua , Asarpota Jyotsna , Ge Haoyou , Hernandez Cristina , Bansal Yogesh , Rodriguez Jose
Published: October 2020

Implementing large-scale projects within a company are challenging tasks and often provide a good learning curve that can be beneficial to understand the complexity of the work involved. An integrated subsurface to surface asset modeling solution was implemented at the country level to automate production capacity planning while optimizing shortfall and opportunity identification (Hafez et al., 2018).

Several structured business processes support the developed system; it orchestrates the analytical processes followed by the corresponding approval system. A robust data management process was implemented and backed with a business process that includes more than 150 configurable exception rules. Besides, the developed solution leverages the rigor of the first principle and data-driven models to provide a desired and stable outcome ranging from potential evaluation, quota definition, capacity management, business plan validation, and other business processes. The developed solution can isolate wells, sectors, reservoirs, and/or fields for further evaluation. Given the challenge of balancing market demand with profits and subsurface deliverability, a time-efficient, balanced, and integrated solution is expected to provide an edge to an organization in this competitive environment.

The Integrated Capacity Model (ICM) system has already been utilized for capacity and deliverability of 2019 and 2020 ADNOC business plans demonstrating 99% agreement with field capacity tests. The system shown +3% profit gains through various production optimization scenarios, while recommending which assets, fields, and/or reservoirs can be targeted to achieve those targets.

Developing and implementing the solution at such a large scale surfaced various challenges at organizational, infrastructure, and solutions/workflows. This paper discusses those challenges and the ‘lessons’ learned during the implementation of this solution. Various value-added use cases are presented.
Production Enhancement In Subsea Fields Through Using Intelligent Completion
Authors: Taher Shetia Mohamed ahmed , selim Islam Elsayed
Published: October 2020

This paper shares The Delta Deep Marine (DDM) experience in developing stacked reservoirs subsea fields by implementing smart completion for reservoir management, surveillance & production sustainability.

Smart well system are composed of permanent downhole sensors & downhole flow control valves that allow recording, evaluating, & actively managing production in real time remotely without any well interventions, which facilitate to improve reservoir management strategy. Once a smart well is completed, valves can independently control each zone of the well, such as controlling zone production when it starts producing water, shutting water-flooded zones or in defensive mode, avoid sand production by adjusting of smart valves settings to safe guard against losing the well.

This paper contains different case studies in applying smart completion & their positive effects in the field development plans. The benefits of optimal application of smart well completion technology in DDM are numerous. These include reducing number of development wells so reduce CAPEX, developing marginal opportunities to improve economics, avoiding well intervention for zonal control to reduce the OPEX, reducing water production to improve subsea network efficiency & reduce water-handling issues, reducing geological uncertainty by proper frequent zonal test, reducing risk of losing the well by control each zone independently to avoid sanding, managing commingled reservoirs with different characterization properly & maximizing reserves. In addition to auto gas lift oil zones without a need to subsea artificial lift infrastructure that allows completing oil zones as an upside gain.

Smart completion was identified as the best option to meet deepwater requirements in producing this field with minimum number of wells without sacrificing targeted production profiles.