bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maximizing Co-Activity Operation and Mastering Drilling Practice as Effective Strategies for Marginal Field Development
Authors: Hadistira Praja , Yuda Bintang Kusuma , Setiohadi Setiohadi , Yudhatama Muhammad Alfianoor , Wijaya Ryan Aditia , Wiharja Andre , Agriawan Crisa 
Published: October 2021

Abstract
A limited remaining reserve is one of the challenges commonly found in mature field development. Swamp fields in the Mahakam block is an example of mature field development which leads to a marginal operation. Delivering wells more economically is one of the key points to survive during those conditions. Rig operation with a significant daily expenditure could be a way for improvement to yield economic wells.
In general, an efficient rig operation would deliver wells in a shorter duration and at a lower cost. In order to lessen the well duration, two aspects could be improved: performing co-activity operation to shorten the horizontal time (preparation) and mastering drilling practices to shorten the vertical time (drilling). In the co-activity operations aspect, various initiatives have been implemented, such as rigless operations, batch drilling, and offline or simultaneous activities. While in the drilling practices aspect, drilling parameters, bit design, connection practice, and team motivation were the areas that have been improved. This paper will elaborate further on those initiatives.
Implementing massive co-activity operations and the best drilling practices have demonstrated a significant time saving of 24% for the shallow well (final depth around 1800 m) and 27% for the deep well (final depth around 4300 m) in the block. These practices have also made a new record of the fastest well completion in 2.17 days and the highest drilling ROP for 141 m/hour with drilling 2303 m in the first 24 hours. The record of most drilled length in 24 hours is the world best performance of RSS BHA as per Directional Driller Company worldwide record. As a result, the 2020 average cost of the shallow well was 2.6 MUSD while the deep well was 4.1 MUSD.
Those massive co-activity operations and drilling practices have been properly executed since 2019 without any safety incident and related NPT. The positive results have helped the development project to survive in marginal conditions.
Kedung Keris Full Well Stream Pipeline Fiber Optic Leak Detection System
Authors: Chairunissa Cindy , Amanu Deny Kalfarosi , Astari Grizki , Indrayana Eska 
Published: October 2021

Abstract
Kedung Keris (KK) is a sour oil field based in Cepu Block, Indonesia. KK field was originally planned to have a processing facility with separate pipelines to deliver crude & produced water, while the gas was planned to be flared. To reduce cost, this concept was changed to a wellpad with full well stream pipeline with new technology of Fiber Optic Leak Detection Sensing System (LDSS) as a key enabler.
The fiber optic LDSS functions by leveraging fiber optic cable attached to the pipeline to detect leak as well as intrusion to the pipeline's Right-of-Way through real-time analysis of physical characteristics of a leak and intrusion, such as changes in temperature, pressure, ground strain and acoustics.
The implementation of LDSS, together with other safeguards built into the pipeline design, operations and maintenance, allowed the KK Project to eliminate the separation facility at KK wellpad and an additional water pipeline. It also reduces the flaring by billions of standard cubic feet of gas cumulative until end of PSC life as originally all gas planned to be flared. The change of KK Project concept altogether yielded tens of millions of US dollar gross cost savings (~30% of CAPEX + OPEX reduction) following the KK startup in late 2019. The installed LDSS proven to detect leak for up to few meters location accuracy and has intrusion detection capability. KK Project has pioneered the implementation of fiber optic leak detection system for Indonesia oil and gas companies. This work provided further insight to the utilization of such technology in full well stream pipeline where traditional leak detection system implementation will not be acceptable. Consecutively, full well stream pipeline deployment can lead to future CAPEX + OPEX efficiency in facility project design and operation, as well as flaring reduction opportunity.
A Novel Design Method for Optimizing the Diverter Dosage in Hydraulic Fracturing Using Three-Dimensionally Printed Fractures
Authors: Wang Meng , Che Mingguang , Zeng Bo , Song Yi , Jiang Yun , Fan Meng , Wang Yonghui , Wang Xin , Zhu Guangyou , Guo Wei 
Published: October 2021

Abstract
Application of diversion agents in temporarily plugging fracturing of horizontal wells of shale has becoming more and more popular. Nevertheless, the studies on determining the diverter dosage are below adequacy. A novel approach based on laboratory experiments, logging data, rock mechanics tests and fracture simulation was proposed to optimizing the dosage of diversion agents. The optimization model is based on the classic Darcy Law. A pair of 3D-printed rock plates with rugged faces was combined to simulate the coarse hydraulic fractures with the width of 2.0 ~ 7.0 mm. The mixture of the diversion agents and slickwater was dynamically injected to simulate the fracture in Temco fracture conductivity system to mimic the practical treatment to temporarily plugging the fracture. The permeability of the temporary plugging zone in the 3D-printed fractures was measured in order to optimize the dosage of the selected diversion agents. The value of Pnet (also the value of ΔP in Darcy Formula) required for creation of new branched fractures was determined using the Warpinski-Teufel Failure Rules. The hydraulic fractures of target stages were simulated to obtain the widths and heights. The experimental results proved that the selected suite of the diversion agents can temporarily plug the 3D-printed fractures of 2.0 ~ 7.0 mm with blocking pressure up to 15 MPa. The measured permeability of the resulting plugging zones was 0.724 ~ 0.933 D (averaging 0.837 D). The value of Pnet required for creation of branched fractures in shale of WY area (main shale gas payzone of China) was determined as 0.4 ~ 15.6 MPa (averaging 7.9 MPa) which means the natural fractures and/or weak planes with approaching angle less than 70° could be opened to increase the SRV. The typical dosage of the diversion agents used for one stage of the horizontal wells (averaging TVD 3600 m) was calculated as 232 ~ 310 kg. The optimization method was applied to the design job of temporarily plugging fracturing of two shale gas wells. The observed surface pressure rise after injection of diversion agents was 0.6 ~ 11.7 MPa (averaging 4.7 MPa) and the monitored microseismic events of the test stages were 37% more than those of the offset stages.
Optimization of Liquid Accumulation and Gas Injection Duration in Intermitter for Maximizing Production: Case Study
Authors: Ranjan Abhishek , Kumar Rajan , Singh Chandra Shekhar , Lama Tshering 
Published: October 2021

Abstract
Gas lift is the process of injecting gas into the tubing at a predetermined depth in order to lift the crude oil to the surface. Gas lift is applied to a well when the reservoir pressure falls to such a level that it does not produce without application of external energy. There are mainly two types of gas lift which are Continuous and Intermittent gas lift. This paper deals with the theoretical determination of relationship between liquid accumulation and gas injection duration in an intermittent gas lift well and how this knowledge can be combined with the experience of Engineers to maximize the production of a well. In order to find the relationship between the given durations, a simple mathematical approach with the assumption that the gas injection time is independent of liquid accumulation time is followed. We, then apply various tools of mathematics such as the principles of maxima and minima, Leibnitz theorem, definition of the slope of a line etc. to finally prove the interdependence of liquid accumulation and gas injection time at which the well can produce at its maximum capacity. This interdependence is plotted on a separate graph with the given times on two axis. This curve represents the values at which the reservoir inflow is maximised and hence another curve representing the tubing outflow is drawn on the same graph to intersect the former curve at the optimum value of liquid accumulation and gas injection time. The paper also discusses the physical significance of the cases in which the two curves do not intersect and its possible solutions which vary in accordance with the experience of engineers and conditions of well. Our mathematical calculation led to an astonishing result that the interdependence between the two given durations is elegant and can be easily found without the use of computer in a very short interval of time. The result indicated that if a tangent is drawn from a point representing gas injection time to the graph of accumulation height versus time, it touches the graph at the value of liquid accumulation time at which the production of well is maximized. This novel approach to determine the value of time in an intermitter or time cycle controller in an intermittent well can be proved to be a boon for gas lift optimizers who would otherwise spend a large part of the time in setting the value on hit and trial basis. The graphical method can determine the optimum value in a shorter interval of time and with greater accuracy saving companies from extra man-hours and unscientific approach to optimizing any intermittent gas lift well.
Integration of Self Organizing Map and Date Driven Methods to Predict Oil Formation Volume Factor: North Africa Crude Oil Examples
Authors: Alusta Gamal , Algdamsi Hossein , Amtereg Ahmed , Agnia Ammar , Alkouh Ahmed , Kcharem Bacem 
Published: October 2021

Abstract
In this paper we introduce for the first time an innovative approach for deriving Oil Formation Volume Factor (Bo) by mean of artificial intelligence method. In a new proposed application Self-Organizing Map (SOM) technology has been merged with statistical prediction methods integrating in a single step dimensionality reduction, extraction of input data structure pattern and prediction of formation volume factor Bo. The SOM neural network method applies an unsupervised training algorithm combined with back propagation neural network BPNN to subdivide the entire set of PVT input into different patterns identifying a set of data that have something in common and run individual MLFF ANN models for each specific PVT cluster and computing Bo. PVT data for more than two hundred oil samples (total of 804 data points) were collected from the north African region representing different basin and covering a greater geographical area were used in this study. To establish clear Bound on the accuracy of Bo determination several statistical parameters and terminology included in the presentation of the result from SOM-Neural Network solution. the main outcome is the reduction of error obtained by the new proposed competitive Learning Structure integration of SOM and MLFF ANN to less than 1 % compared to other method. however also investigated in this work five independents means of model driven and data driven approach for estimating Bo theses are 1) Optimal Transformations for Multiple Regression as introduced by (McCain, 1998) using alternating conditional expectations (ACE) for selecting multiple regression transformations 2), Genetic programing and heuristic modeling using Symbolic Regression (SR) and cross validation for model automatic tuning 3) Machine learning predictive model (Nearest Neighbor Regression, Kernel Ridge regression, Gaussian Process Regression (GPR), Random Forest Regression (RF), Support Vector Regression (SVM), Decision Tree Regression (DT), Gradient Boosting Machine Regression (GBM), Group modeling data handling (GMDH). Regression Model Accuracy Metrics (Average absolute relative error, R-square), diagnostic plot was used to address the more adequate techniques and model for predicting Bo.
PiNTAR Gas Lift System: Paving the Way for Automated Field Implementation
Authors: Sajjad Farasdaq Muchibbus , Wirawan Alvin Derry , Rachmadi Dharmawan Alfian , Suganda Wingky , Susanto Dany , Gusman Muryadi 
Published: October 2021

Abstract
As oil and gas development in Indonesia is shifting towards offshore environment, automation is essential for reducing operating cost. PHE ONWJ as the biggest oil and gas operator in Indonesia develops an automated field operation for gas lift optimization, called PiNTAR.
PHE ONWJ has been operating gas lift wells for almost 40 years. The biggest challenge is how to efficiently conduct the business operations in offshore environment. The current regular operations (for instance production monitoring) are conducted manually in monthly basis. It is time-consuming and requires long time for trouble shooting.
PiNTAR is designed by PHE ONWJ by integrating smart signal system that can be operated remotely without having to be physically presence at the site. The system is integrated with SCADA sensors, satellite system and fully electronic transmitter that sends production data and related parameters to PHE ONWJ head office to be analyzed 24/7 and mitigated if necessary.
PiNTAR has been implemented on more than 50 wells in PHE ONWJ working areas. PHE ONWJ also provides interactive Graphical User Interface based software for monitoring and production adjustment purposes. Standardization is also performed therefore PiNTAR can be implemented in a wider area, with different gas lift situations.
PiNTAR enables operators to quickly diagnose flow irregularities ranging from adjusting injected Gas Liquid Ratio (GLR) to minimize annular flow, modify choke openings, dynamic reallocation of injected gas from multiple well systems, and also allows the team to comprehend a significant amount of flow characteristics in gas lifted wells as measurements are taken in a very small-time frame, ranging from minutes to seconds. PiNTAR also enables automated production test that enables the construction of real time Gas Lift Performance Curve, which reduces operator workload and enables dynamic gas lift optimization. Implementation of PiNTAR also reduces HSSE risks for rope jumping operations in offshore and increases efficiency of fuel and personnel timing in platform.
The publication presents a success story of gas lift automated optimization using in-house development from PHE ONWJ called PiNTAR. Significant monetary efficiency as well as production increase has been observed during the implementation, encouraging the company to pursue further field automation efforts.
Array Production Survey Accurately Pinpoints Water Shut-Off Location and Strengthen the Understanding on Remaining Potential of a Giant Carbonate Gas Field, Offshore East Malaysia
Authors: Ahmad Noor Afiqah , Chieng Zhin Houng , Jelie Anie , Abdul Rahman Hazrina , M Amin M Farid , Foo Nicholas Kwang Hui , Zakeria Ahmad Fakrudin , Sidek Sulaiman , Yahya Fadzil , Ramli Syamim , Suhari Azahari , Abd Manan Mohd Zahir 
Published: October 2021

Abstract
Over the years, Multiple Array Production Suite (MAPS) has been run several times in Offshore Peninsular Malaysia but never in Offshore East of Malaysia. Field A is located 260km North-North West of Bintulu, Offshore Sarawak and was discovered in 1992 with first gas produced in 2004. One of the many challenges currently faced in managing the field is the prediction and handling of water breakthrough at the existing producers. Based on historical data, water breakthrough from carbonate Zone T begin around 2010 which then followed by series of Water Shut-Off (WSO) campaign. To strengthen the understanding, evaluate the remaining potential and to optimize near term well and reservoir management of the field, an integrated remedial approach is essential. Well-AA was identified for mechanical WSO in an effort to remediate high water production and improve well productivity. The target well was chosen as the well unable to sustain production after a rapid tubing pressure drop due to the highest water production in the field. Moreover, its production had to be capped due to the water production constraints at the receiving hub. Production Logging (PL) was planned across the carbonate sections to accurately identify the appropriate zones for WSO operations.
The long horizontal section and high water production typically create a stratified flow regime that forces a smaller volume of hydrocarbon to flow on the high side of the well, hence the conventional PL technology would have been unable to deliver accurate and insightful results. As such, the MAPS technology was run for an initial assessment to identify the water producing zones. MAPS was deployed using wireline tractor and was combined with the Noise Tool (NTO) to provide a comprehensive 3D image of the multi-phase flow profile across the entire wellbore and to investigate the integrity of annular swell packers located in between the carbonate sections.
This paper illustrates the best practices involved in the successful downhole Production Logging with a Multiple Array Production Suite and Digital Noise Tool (PL-MAPS-NTO) toolstring, which served as the key input in determining the WSO treatment depth and strategy in Well-AA, that may lead to a potential gain of 10.8MMscf/d.
Optimized Clay Control Fracturing Fluid Used in a Highly Water-Sensitive Tight Oil Reservoir Hydraulic Fracturing Application in Xinjiang Oil Field: Case Study
Authors: Mao Xinjun , Chen Chaofeng , Gan Renzhong , Zhou Shubo , Wang Zichao , Zhao Zhoumin 
Published: October 2021

Abstract
The candidate wells are tight oil wells and most of the wells in the area have a low recovery rate of fracturing fluid after fracturing treatment. The lithology is glutenite with weak cementation and a high sensitivity tendency. This paper presents the process of sensitivity evaluation and fracturing fluid evaluation. Also, this paper introduces a customized and optimized clay control fracturing fluid wells in a highly sensitive reservoir.
Per local national standard, traditional methods of swelling test (ST) and x-ray diffraction (XRD) were employed for qualitative formation cutting analysis. An innovative trial was then developed to evaluate cores quantitatively by water sensitivity. A clay stabilizer was then chosen to be used for the highly sensitive cores and regain permeability testing of the broken fracturing fluid was performed. Based on the analysis and evaluation, a customized treatment design was initiated for the hydraulic fracturing treatment.
The qualitative evaluation showed the rock is highly water sensitive and the cores easily collapse because of weak cementation. No flow could be established during traditional core flow tests with brine. The newly developed method used kerosene as the working fluid to prevent the cores from contact with water or brine. The core flow tests resulted in a velocity sensitivity damage rate of 92%, which is considered as highly velocity sensitive. Accordingly, a special clay stabilizer was chosen to be used in the fracturing fluid and the permeability damage of the broken fracturing fluid is only 26.9%(Table 16).
Field results have shown that the fracturing fluid recovery rate in treated wells is higher than the area average level and treated wells have significant oil production increase. The innovative clay control fracturing fluid and its field application reduces the influence of water and velocity sensitivity. The customized treatment with special clay stabilizer helps increase the recovery rate of fracturing fluid in reservoirs with severe clay stability and weak cementation issues.
Towards 1 Million Barrels Oil Per Day in 2030: Visual Analytics for Artificial Lift Performance Optimization in Indonesia
Authors: Falach Achmad Rocky , Warasta Ageng , Ihsan Alfandra , Dewi Amalia Kusuma , Safrizal Heri , Perfibita Randy , Kauripan Satria Panji 
Published: October 2021

Abstract
One of the strategies to achieve Indonesia's main goal to produce one million barrels oil per day in 2030 is to maintain existing production volume. The key of maintain the existing production is to optimize artificial lift performance used in oil wells, because 96% of oil wells in Indonesia had installed artificial lifts and their performance will significantly affect the production decline rate. This approach aims to create a simple data visualization from macro perspective, to evaluate the artificial lift performance of all oil wells in Indonesia and to find a solution to optimize their performance.
This method is started by collecting the main parameters that describes the artificial lift performance such as artificial lift type, historical run life, historical operating cost, production rate, reservoir depth, type of fluid as well as additional issues from each field in Indonesia. After the data is gathered, the next step is to cluster the usage of various artificial lifts in Indonesia, which have similarities such as area, crude type, depth, rate, and operational problems, in terms of comparison between the optimum case and non-optimum one. Finally, from the non-optimum one, it will be evaluated on more detailed programs for further optimization. This evaluation process is carried out by visualizing all the data gathered using some informative dashboards. The digitalization is expected to help the improvement of evaluation time and to support decision processes.
By implementing this method, several success cases were demonstrated in 2020, like optimizing Sucker Rod Pump (SRP) component in one of the fields in Sumatra, with the gain around 120 BOPD, Gas lift and SRP to Electric Submersible Pump (ESP) conversion in one of the fields in Kalimantan with 160 BOPD production outcome, switching normal ESP rate to lower rate ESP which resulted from double run life compared with the previous one, and also conversion from SRP to HPU that can extend its run life, while creating cost efficiency. From those results, it shows the benefit of the dashboards created for artificial lift optimization, especially from Government point of view. Furthermore, there are around 50 wells that will be evaluated in detail for optimization program.
The visual analytics of the dashboards, for example, will help the evaluation process all at once providing positive impacts on artificial lift optimalization program. In the future, we hope that these dashboards could be developed further, by combining the implementation of machine learning, like fuzzy logic methods or neural network, to enhance the operator performance and to improve production efficiency toward the achievement of one million barrels oil per day in 2030.