bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hybrid Drill Bit Technology on Performance Motor Bottom Hole Assembly Yields Breakthrough Drilling Performance in Kuwait
Authors: Al-Baghli Waleed , Al-Salamin Mohammad , Sulaiman Sulaiman , Abdelhamid Atef , Alnemer Ali , Pandya Mehul , Agawani Waleed 
Published: October 2019

Abstract
Operators in the current volatile oil and gas industry must optimise drilling performance and minimize well cost. Various drilling tools and methods have been implemented over the years to improve drilling efficiency and to reduce the non-productive time (NPT) while drilling through challenging formations. Many North Kuwait onshore wells are drilled with conventional drill bit technologies, such as tungsten carbide insert (TCI) and polycrystalline diamond compact (PDC) bits on either rotary or performance motor bottom hole assemblies (BHA). This paper discusses the breakthrough drilling performance of 16-in. hybrid drill bit technology on a performance motor BHA, delivering outstanding results and savings for the operator. The typical 16-in. vertical section ranges from 4000 ft. to 5000 ft., and contains limestone and sandstone with interbedded layers of shale and streaks of anhydrite with high variance in the unconfined compressive strength (UCS) across these formations.
The downhole environment is unsuitable for PDC bits due to impact damage from the variable UCS, and TCI bits provide unsatisfactory rates of penetration (ROP) requiring a new drilling approach for the application. Poor dull conditions combined with the long section led to low overall ROP, further indicating the need for a new class of bit.
The engineering process involved reviewing: –Current TCI and PDC cutting structure designs–Surface drilling parameters applied–Post-run dull analysis from current bit designs–Previous TCI and PDC bit design performance on rotary and motor BHA–Hybrid design performance on rotary BHA
A collaborative technical analysis identified key performance objectives to ensure a step change in section drilling. Hybrid drill bit technology was deployed on a performance motor BHA to enhance the ROP. The hybrid bit enhanced the ROP by 153% with a 52% reduction in cost per foot compared to the average TCI performance in this field, saving the operator 2.2 days and over $ 0.4 Million operational cost.
The hybrid drill bit design demonstrated its ability to serve as an alternative to conventional technologies and showed the potential for efficient drilling and reduction of NPT over multiple wells, assisting operators in the current cost-sensitive industry environment.
Back to Basics: How a Field in Offshore Sarawak Optimize Production and Maximize Recovery Via Analytical Approach
Authors: Abd Rahman Noor Shakila , Zamzuri Mohd Dzulfahmi , Abd Wahid Muhammad Izad , Jamaluddin M Helmi 
Published: October 2019

Abstract
Field XX is a mature field located in offshore Sarawak with relatively low RF due to reservoir complexity and compartmentalization. Previous development campaigns focused on specific compartments, while future development plans are targeting less developed compartments to increase the field-wide recovery. This paper is intended to discuss the methods and the success story of production optimization and recovery maximization effort from developed reservoirs: Classical Method: Data and analysis integration allows identification of unswept oil and behind casing opportunities (BCO). The approach begins with incorporating reservoir maps and correlations with current fluid contacts (from reservoir performance and logging data), pressure trending, production bubble maps etc. Identified opportunities are further evaluated using MBAL and Prosper models to de-risk the potential.Dumpflooding: From wellbore utilization review and reservoir performance analysis, in situ dumpflood candidates can be identified. In Field XX, most wells are completed in multiple sand sequences, which open up the opportunity to utilize water-producing reservoir to naturally flood the depleted reservoir via pressure difference in shut-in conditions.Drainage Optimization: Over the production life, numerous development wells were drilled and completed targeting specific reservoirs. After decades of production, adjacent wells started to feel the interference of the other, creating a sub-optimal production condition. Via gross rate vs. top node parameter analysis, well drainage optimization opportunity can be achieved by shutting less productive well to allow the better to continue producing at a higher potential.
Using analytical reservoir engineering, Field XX managed to achieve the following: (A) identified 2 unswept/attic oil BCO to increase RF in respective reservoir by 2-4%; (B) implemented drainage optimization to increase the technical potential by 40% and delay water table progression by shutting in the downdip neighbouring well; and (C) identified a dumpflood candidate to provide pressure support prior to a more comprehensive water injection project in the future.
Management of Artificial Lift Planning & Deployment for Improved Field Development Plan
Authors: Haryanto Elin , Yersaiyn Saltanat , Shah Abdur Rahman , Su Shi , Bouchet Francois 
Published: October 2019

Abstract
Artificial lift is generally required to extend field-life beyond the period of natural flow. In the course of the reviews and studies we performed, we noted artificial lift had not been given sufficient consideration at initial design phase. Due to the pressure to maintain the field production, operators often choose a phased artificial lift deployment to cope with the learning curve, risks and uncertainties, which typically includes: ▪A first phase (Phase-1) of artificial lift is screening and concept testing to evaluate artificial lift options;▪A second phase (Phase-2) involves deployment to a group of wells for a selected option;▪A final phase (Phase-3) is the full field implementation.
This paper presents an efficient and effective workflow to select the most suitable candidates for Phase-2. Lessons learnt based on the implementation of workflow in real-life case studies will be shared as well: ▪First, a well selection process is performed to review inactive strings and/or low performers that are most impacted by such issues as reservoir pressure declined / high water production. Cased-hole saturation logs (PNC log) and static pressure log measurements are used to build an understanding of areal pressure and water saturation distribution and to further identify localized pressure sinks and watered-out areas. The understanding gained upon reviewing the well-based surveillance data is used to identify candidates for artificial lift application.▪Then, the well candidates which are grouped by categories of issues and different reactivation options are screened for each group of wells. A score-based ranking process is applied to sort candidates on urgency, value or impact of artificial lift and possibly other criteria, using production history and surveillance data.▪Finally, results per well are reconsolidated to reservoir / field level and used to support a field-wide concept, which allows to extract valuable field scale requirements (e.g. the determination of the gas-lift volume requirement for gas-lift planning etc.).
This workflow greately helps to understand the root cause of performance issues and to select the most suitable artificial lift concept (including considering well pre-conditioning needs such as water shut-off). It leads to exploring and defining artificial lift concepts and helps to focus on the field development plan and detail engineering study at a very early stage.
Reservoir Recovery Estimation Using Data Analytics and Neural Network Based Analogue Study
Authors: Chen Yajing , Zhu Zhouyuan , Lu Yangxiao , Hu Changhao , Gao Fei , Li Wei , Sun Nian , Feng Tian 
Published: October 2019

Abstract
Reservoir analogue study, which is different with flow physics based prediction methods such as reservoir simulation, is based on human experience and knowledge from skilled reservoir engineers. In this work, we present a new workflow to replace the human knowledge-based analogue studies with data analytics and machine learning techniques.
First, we collect reservoir properties, development parameters, and historical recovery data for 1381 actual U.S. oilfields from Tertiary Oil Recovery Information System (TORIS) by U.S. Department of Energy. We conduct extensive data cleaning for outliers and missing values. Then, we determine the most important determining factors for recovery factors. We further use single-variable and bi-variable analysis to understand relationship between recovery factor and determining factors. Finally, we use train an Artificial Neural Network (ANN) model to make recovery factors predictions.
We have found that the recovery factors mostly depend on 19 principal factors, a reduction from a total of more than 70 properties originally in TORIS. We randomly select data from 90% of these oilfields as training set for machine learning. The predictability and accuracy of such methodology is tested by making recovery forecasts for the remaining 10% oilfields and by comparing the forecasts with the actual recovery factors. Eventually, the average error in recovery factor predicted by the trained ANN model is about 10%. Overall, this methodology has shown strong performance in computer assisted analogue study, which shows minimum requirements on human knowledge and hands-on work to study these 1381 oilfields.
This work provides a new workflow of using data analytics and machine learning techniques for reservoir analogues studies. Reservoir engineering software systematically built based on this methodology can serve as more efficient and accurate predictive tool in studying reservoir analogues.
2nd Chance - An Interactive HSEQ Event and Initiative Reporting System for Improving Performance in Well Intervention Division
Authors: Siswanto Agus , Therademaker Ricky , Ramli Rafiansjah 
Published: October 2019

Abstract
The Health, Safety, Environment and Quality (HSEQ) reporting system is used in Well Intervention (WLI) Division of PT Pertamina Hulu Mahakam as one of Oil and Gas Company. WLI operations are considered massive with 21 barges and 890 workers. The barges are spread out onto 6 production sites. They can generate substandard act / situation, Downgraded Situation (DGS), incident, or deviation toward the HSEQ procedure. It shall be monitored and rectified to avoid any escalation and avoid repetition.
As part of HSEQ Management System implementation, HSEQ initiative program need to be monitored its progress to achieve Company's Objective (lagging indicator). The initiatives consist of audit/ inspection, emergency drill, meeting, and visit.
The need of database recording system is unavoidable to manage the operations accordingly. It triggers the development of reliable and user friendly application to learn from the event and initiative reporting system. The application is officially launched in mid of 2017 after 6 months of development.
2nd Chance is developed internally by considering Company Rule, operational user expectation and experience operating in Mahakam field. The reporting system consists of HSEQ Anomaly, Downgraded Situation (DGS), Incident and Initiative. The tool is accessible everywhere with Company's network access (intranet), capable to accommodate all essential information with smart interactive features i.e. user friendly and able to avoid unnecessary mistakes. It is equipped with automatic graphical dashboard to analyze the trends.
Company's Objective is to obtain zero Loss Time Incident (LTI) operation could be achieved by the management of learning from the event as continual improvement process. WLI Division achieves 540 days without LTI with 5.33 million man-hours in 2017 - 2019.
VSD Setting: ESP Motor Current-Feedback, An Effective Approach to Mitigate High Gas Interference Problem in Gassy ESP Well - Case Study SK-0178
Authors: Amijaya Winandar , Kusuma Hendra , Narso Narso , Sudibyo Geraldus Yudhanto 
Published: October 2019

Abstract
Gas Interference is one of the main difficulties in ESP Operation. High gas interference might reduce the pump volumetric efficiency (lower liquid production) and in the worst situation might stop the pump operation due to Gas Lock. In longer operation, it might even damage the motor due to frequent start-stop.
ESP at SK-0178 installed in Nov-2016, and directly having problem with High Gas Interference & Gas lock (frequent underload alarm) resulting 3-4 times shutdown daily. Several troubleshooting steps have been taken:
Venting the annulus gas: Resulting no shutdown, could handle the gas issue but not an environmentally friendly solution and wasting valuable gas production (200 KSCFD) VSD - PIP (Pump Intake Pressure) feedback: Resulting no shutdown, but ESP operated with fluctuating load and with lower production rate (gas interference, dropped by 40-60 BOPD)
Detailed discussion with technology provider and reference case study come up with a proposal to trial New VSD Logic: Motor Current Feedback. The logic worked immediately after it is applied. All pump parameters (Frequency-Hz, Motor Load-A, PIP-Psig) shortly monitored to be stable unlike the previous PIP-feedback mode. The logic works better for high gas interference condition. It keeps the pump from having an accumulated gas inside the impeller-diffuser, hence preventing the pump from the possibility of having gas lock condition. Well test performed after the mode-change also showing a return to normal production. In longer monitoring period, the pump also showing a stable operation, thus we can say the approach is successfully mitigating the high gas interference ESP case in SK-0178: No shutdown, saving 200-KSCFD gas and 120-BOPD production.
Sumatera Operation SMO Integrated Optimisation Decision Support Center IODSC Success in Embracing Digitalisation and Innovation to Deliver Business Results
Authors: Susanto Ivan 
Published: October 2019

Abstract
This paper will describe the success of Chevron Pacific Indonesia's (PT. CPI) Sumatera Operation (SMO) to deliver improved business results through the implementation of an Integrated Optimization Decision Support Center (IODSC). The SMO IODSC is focused on value optimization across the Rokan Production Sharing Contract (PSC) by developing and implementing digital solutions ranging from the simple, such as Short Message Service (SMS) gateway to monitor rig status, through to the more advanced, such as Artificial Intelligence to identify failing equipment. Value creation was achieved by the systematic adoption of digital solutions to reduce lost production opportunity (LPO), reduce expenses, improve energy efficiency and optimize hydrocarbon production. Key to this systematic adoption is IODSC's Integrated Exception Management (IEM) system. IEM supports CPI employees in their daily tasks by:
Managing large amounts of data captured each day and using data science to change it to actionable information. Capturing exception criteria based on Subject Matter Experts (SME) knowledge that automatically identifies and prioritizes wells and equipment operating outside the desired condition (exception signals). Housing workflows to enable review, action and close-out of the exception signals.
IEM provides "one-stop exception review" and "start to finish workflow" capabilities that documents accountability for each step of the workflow and the time taken to complete. IEM allows for the exception criteria to be defined by physical principles, subject matter expert (SME) knowledge, or Artificial Intelligence (AI)-based techniques.
As a result of this systematic implementation of improved workflows and digital solutions, within 2 years of commencement the IODSC exceeded it's 5 year value creation target.
Application of Design of Experiments for Well Pattern Optimization in Umiat Oil Field: A Natural Petroleum Reserve of Alaska Case Study
Authors: Gurav Yojana S. , Dandekar Abhijit Yeshwant , Patil Shirish L. , Patwardhan Samarth D. 
Published: October 2019

Abstract
Umiat field, located in Alaska North Slope (ANS) poses unique development challenges because of its remote location and permafrost within the reservoir. This hinders the field development, and further leads to a potential low expected oil recovery. The objective of this work is to assess various possible well patterns of the Umiat field development, and perform a detailed parametric study to maximize oil recovery and minimize well costs using statistical methods.
Design of Experiments (DoE) is implemented to design simulation runs for characterizing system behavior using the effect of certain critical parameters, such as well type, horizontal well length, well pattern geometry, and injection/production constraints on oil recovery. After carrying out simulation runs using a commercially available simulation software, well cost is estimated for each simulation case. Response Surface Methodology (RSM) is used for optimization of well pattern parameters. The parameters, their interactions and response are modeled into a mathematical equation to maximize oil recovery and minimize well cost.
Economics plays a key role in deciding the best well pattern for any field during the field development phase. Hence, while solving the optimization problem, well costs have been incorporated in the analysis. Thus, based on the results of the study performed on selected parameters, using interdependence of the above mentioned methodologies, optimum combinations of variables for maximizing oil recovery and minimizing well cost will be obtained. Additionally, reservoir level optimization assists in providing a much needed platform for solving the integrated production optimization problem involving parameters relevant at different levels, such as reservoir, wells and field. As a result, this optimum well pattern methodology will help ensure optimum oil recovery in the otherwise economically unattractive field, and can provide significant insights into developing the field more efficiently.
Computational algorithms are gaining popularity for solving optimization problems, as opposed to manual simulations. DoE is effective, simple to use and saves computational time, when compared to algorithms. Although DoE has been used widely in the oil industry, its application in domains like well pattern optimization is novel. This paper presents a case study for the application of DoE and RSM to well optimization in a real existing field, considering all possible scenarios and variables.
Revealing Hidden Potentials to Maintain Production by Using Integrated Petrophysical Interpretation Techniques in Mahakam Mature Fields
Authors: Hidayat Haris , Supriady Supriady , Anwar Taufik , Ariestya Gilang , Giriansyah Bayu 
Published: October 2019

Abstract
Hydrocarbon identification in mature fields located in Mahakam area is very challenging due to thin and multi layers of reservoir geometry, wide range of water salinity in deltaic environment, depletion and water-rise phenomena in highly producing zones. There are numerous possible gas reservoirs which were dubious and not included in perforation targets due to poor quality sand or risk of water production which could jeopardize the entire well potential. These possible gas reservoirs need to be re-evaluated in order to add perforation targets portfolio in maintaining field production when less new wells drilled.
An integrated methodology has been continuously developed and calibrated to reduce uncertainty, hence elevate confidence level of fluid interpretation by combining the existing and recently developed techniques in Mahakam fields. The existing techniques are (1) Conventional Qualitative interpretation, (2) True-Wet Resistivity separation, and (3) Gas-Oil Volumes from simultaneous solution. The new developed techniques are (4) Swirr-SWT comparison, (5) Water Saturation Array Gradient with salinity, (6) AutoFluid resistivity specific cut-off, (7) Dual logs sliding average analysis, (8) Neutron Count Rate, (9) RT-GR cut-off, and (10) Gas Chromatograph dynamic baseline.
In collaboration between petrophysicist, development geologist & reservoir engineering, this new integrated fluid interpretation methodology has been applied to re-evaluate more than 11,000 possible gas reservoirs in Mahakam fields. This effort has revealed around 32% of them as hydrocarbon potential reservoirs with total thickness of 4,195 meters. Those reservoirs are then convincingly re-interpreted as gas bearing reservoirs and included as additional perforation candidates. Some of those reservoirs have been perforated and giving additional gain in maintaining gas production of Mahakam fields.
By capitalizing the existing data, with no additional data acquisition, hence no additional cost, this integrated fluid interpretation methodology, could be implemented in other fields outside Mahakam to find hidden potentials which not identified yet.
Geochemical Modeling of Low Salinity Water Flooding EOR Mechanism
Authors: Chen Quan , Enezi Sultan , Yousef Ali 
Published: October 2019

Abstract
Low salinity water flooding (LSWF) is a cost-effective EOR technique. However, the underlining mechanism of LSWF EOR is still a matter of debate due to the complexity of the Crude Oil/Brine/Rock (COBR) system. The objective of this paper is to study the mechanisms of LSWF EOR processes by means of geochemical modeling.
A reactive transport geochemical modelling approach with a geochemical simulator PHREEQC (pH-REdox-EQuilibrium in C programing language) is applied in this paper to handle complex interplay of different geochemical effects such as ion exchange, rock mineral dissolution, flow and transport during LSWF EOR processes.
This paper proposes and demonstrates a geochemical mechanism for LSWF EOR, i.e., spreading of mineral dissolution waves driven by cation exchange process.
The sandstone reservoirs often contain clays and carbonate cements. Clay minerals are present in some carbonate reservoirs. LSWF disturbs the geochemical equilibrium between connate brine and rock minerals in the reservoirs and results in carbonate dissolution. This study shows that without the presence of clay minerals, carbonate mineral dissolution can only occurs locally close to the inlet of core plug or injection well in the field during LSWF and then new equilibrium between brine and rock minerals is reached. Because of the presence of clay minerals and the nature of cation exchange process, clay surface even more preferentially absorbs divalent cations over mono valiant cations during LSWF. This cation exchange process softens the injected low salinity brine and propagates the softened low salinity brine and therefore carbonate mineral dissolution waves from injection well to production well in the field. The spreading of carbonate mineral dissolution waves and the resulting local pH rise have several field wide consequences: (1) The carbonate mineral dissolution and the resulting local pH increase can occur field wide. (2) Mineral dissolution not only releases oil attached to the mineral surfaces but also creates more fresh water-wet rock surfaces and improves oil recovery of LSWF. (3) Rising pH makes both rock surfaces and acid components of crude oil more negatively charged. The subsequent electrostatic interactions help release of polar components from rock surfaces, and increase the water wetness of the rock surface and therefore improve oil recovery.