The PEP structure in Matindok block in Central Sulawesi has been proven to produce gas reserves in the Minahaki formation based on the first exploration well PEP-001 that was drilled in 2018. The PEP structure has a Miocene carbonate build-up play, and the target reservoir is the M member pinnacle carbonate reef. One of the main challenges in this area is low resolution of seismic data, leading to a high depth uncertainty of top M position. The PEP-001 well was planned to set the 9 ⅝-in casing point above top M. Offset wells did not show any clear markers in the thick shale above M formation, that could have been used for log correlation. In previously drilled offset wells correlation was done conventionally by taking cutting samples and relying on drilling parameters break. However, when PEP-001 was drilled, no apparent drilling break was observed. By the time cuttings reached surface, the bit had drilled into 20-m thickness of M formation. Since casing covered most part of the upper carbonate formation, open hole logging and well testing data were not acquired to delineate target M formation optimally. The second exploration well PEP-002 was planned with an objective to set 9 ⅝-in casing ~5 m above top M to acquire a full interval coverage of coring, open hole wireline logging, and well testing program. This information was critical for optimal reservoir delineation to allow for accurate reserve calculation and future structure development. Conventional correlation (well-seismic pairing and correlation) has proven insufficient for casing point placement and was a lesson learned from PEP-001. The presence of limestone stringers observed in offset wells within proximity of top M presented an additional challenge. The stringers could have been mis-interpreted as the main carbonate body, if interpretation was solely based on cutting samples. Based on these challenges, a technology with the capability to map and detect lithology changes ahead of the bit in real time was required. Real-Time EM Look Ahead technology uses deep directional electromagnetic (EM) technique to detect formation feature ahead of the bit. A feasibility study was done to simulate the tool response and define the placement of transmitter and receivers (spacings) in the BHA, as well as frequency selection based on the resistivity properties from offset wells. Based on the simulation, this technology was expected to detect top M formation as early as 10 m ahead of the bit. While drilling, top M could be resolved at 6 m ahead of the bit with an uncertainty of <1 m, therefore making this the fit-for-purpose technology to place the 9 ⅝-in casing point ~5 m above the M formation. As a result, 9 ⅝-in casing was successfully placed 5 m above top M. High resistivity contrast, that is expected to be top M, was mapped continuously from 10 m ahead of the bit. The decision was to set the casing point at 1706 m MD, 4-5 m from the estimated top M. Coring results and open hole logging in the subsequent 8 ½-in hole section confirmed that top M was at 1711 m MD, 5 m from the casing point, which was precisely as estimated from Real-Time EM Look Ahead Technology. This technology also helped detect thin limestone stringer and differentiate it from the target carbonate formation. It prevented 9 ⅝-in casing to be set ~118 m shallower where the first limestone stringer was observed. This has avoided extra operating days in case of drilling problems due to long exposed shale in the subsequent 8 ½-in hole section. The potential cost savings were estimated at USD 1.35 million for an additional 6-in hole section. Following this success, the same technology will be used in the next planned exploration wells.

The coal-seam gas (CSG) industry has long been considered as a high volume, low cost market. As the industry has matured, the selective application of high-tier technologies has realized a step change in performance and real-time formation evaluation results. We investigated whether a high-tier LWD multi-function service could provide a suite of quantitative real-time measurements in several deviated wells. The key objective was to reduce the amount of non-productive rig time spent waiting for memory data in order to confirm the completion design. Significant savings in rig time could be realised if reliable, high-quality real-time data enabled the early identification of coal seams and permeable aquifers such that the swellable packer and slotted liner completion design could be completed without the need for final memory logs. The area of interest is characterized by thin Jurassic coal seams rather than thick Permian seams. It was critical to accurately identify thin coal beds in real-time whilst maintaining a high rate of penetration (ROP). Low-resolution data would result in poor completion design, underestimation of net coal reserves, and sub-optimal static models. Measuring coal thickness and properties can be difficult due to the fundamental differences between the formation evaluation measurements and their relative axial resolutions. The presence of thin coals can further complicate the interpretation. Another challenge was to optimize the real-time data transmission to prevent any limitation on the key directional drilling data parameters. Conventional LWD logs (gamma ray, nuclear, and resistivity measurements) provide formation evaluation information while drilling. The selection of a rotary steerable system (RSS) was critical as it ensured directional control and avoided any sliding intervals over key aquifers and coal zones, thereby ensuring optimal LWD acquisition. Advanced formation evaluation options of the LWD data also included using dual-pass resistivity inversions for Rt/Rxo to determine the invasion profile in a permeable aquifer zone above the main coal-producing reservoir. Having this information in real-time was critical in guiding well-specific competition decisions. Induction and laterolog-type resistivity tools were run on one well to quantify differences in the measurements and to determine the best resistivity acquisition tool for CSG wells drilled with saline muds in freshwater formations. The results showed that high-tier LWD technologies provide multiple benefits in CSG wells. The project was executed with all directional and logging objectives achieved. Quantitative real-time data was critical for completion decisions including ECP placement together with swellable packer and slotted liner designs. This resulted in significant cost savings which are important to major CSG developments operating within a low-cost operating model. LWD memory data provided a rich suite of additional measurements to complement the real-time data. Memory data was used for advanced reservoir analysis with industry-unique measurements.

Sand production from wells are one of the operators’ biggest nightmare as the cascading effect can cause some major harm to the surface equipment as well as lead to a costly cleanup effort. Sand sampling in gas wells is considered a rare activity due to the difficulty of containing the gas flow. The objective of this paper is to elaborate on why this activity is crucial to be performed in sand prone gas wells and more importantly the value it can bring to the asset owner. The paper will also elaborate further on the benefits of coupling the online sand sampler with the acoustic sand monitors to improve accuracy and reliability of readings The paper will elaborate the major difference in sampling for oil wells and gas wells. Operators of oil fields have the liberty of sampling from an existing sampling point to obtain the sand count. However, obtaining the sand count in a gas well is not as straight forward as it is for oil wells hence the importance of this activity. Quantification of sand produced in gas wells are also a challenge as only amount of sand is reported from the desander flushing. The paper will contain a detailed procedure on the methods to quantify sand production as well as the process flow to determine the max sand free rates safely to meet the objectives of this project. Some of our wells were ‘accused’ of producing sands at certain flowrates. Since the wells were not equipped with any type of permanent sand monitoring equipment, there were no conclusive ways of proving that the wells were sand free. Due to that, the wells flowrates were curtailed to protect the asset from the effect of sand production. With the completion of this activity, we could conclusively prove that the wells were free from producing sands at the existing rates. On top of that, from the process of determining the max sand free rates (MSFR) this activity gave us enough confidence to produce our wells at a proved sand free rate. In conclusion, not only does this activity allow us to prevent further production deferments, this activity also allows us to increase production by beaning up the wells if possible This is a very flexible method that can be used as the main method to sample sand in gas wells. It is a very cost-effective method as well as logistically friendly to mobilize to even offshore fields.

This paper describes the extensive integrated engineering collaboration and optimization process to allow the operator to push the drilling and completion envelope to drill complex ultra extended reach drilling (ERD) wells in a mature field. The Wandoo field is located within WA-14L in the Carnarvon Basin, offshore Western Australia and is wholly owned and operated by Vermilion Oil & Gas Australia Pty Ltd (VOGA). Due to the shallow reservoir depth, extreme ERD profile and the high tortuosity requirement for the wells, significant challenges were identified during the planning stages of the campaign. To optimize well placement, update geological information and reduce collision risk with nearby producing wells, the Reservoir Mapping While Drilling (RMWD) service was run in real-time. The primary objective of the service was to place the well in the optimum position within the reservoir, this included (1) provide early detection of moved oil water contact (MOWC) while approaching well crossings with minimum separation factor to reduce collision risk and geological uncertainties; (2) to steer azimuthally to optimize the placement of the well with respect to the field bounding fault and reduce the drilling risk associated with the intersection of the fault; and (3) to distinguish between the A3 Upper (A3U), A3 Lower (A3L), and B sands to optimize well placement. These challenges were successfully overcome with extensive planning, integrated engineering designs, application of new state-of-the-art technology, good quality real-time data interpretation and a strong execution support from both rig site and town. As the result of good collaborative teamwork in planning and execution, the two highly technically challenging wells were drilled and completed successfully and brought online for production. A number of drilling performance highlights captured during the execution phase were identified as having significantly contributed to the successful completion of the project.

Drilling is considered one of the most challenging and costly operations in the oil and gas industry. Several initiatives were applied to reduce the cost and increase the effectiveness of drilling operations. One of the frequent difficulties that faces these operations is unexpected drilling troubles that take place and stops the operation, resulting in losing a lot of time and money, and could lead to safety issues culminating in a fatality situation. For that, the industry is in continues efforts to prevent drilling troubles. Part of these efforts is utilizing the artificial intelligence (AI) technologies to identify troubles in advance and prevent them before maturing to a serious situation. Multiple approaches were tried; however, errors and significant deviation were observed when comparing the prediction results to the actual drilling data. This could be due to the improper design of the artificial intelligent technology or inappropriate data processing. Therefore, searching for dynamic and adequate artificial intelligent technology and encapsulated data processing model is very essential. This paper presents an effective data-mining methodology to determine the most efficient artificial intelligent technology and the applicable data processing techniques, to identify the early symptoms of drilling troubles in real-time. This methodology is CRISP-DM that stands for Cross Industry Standard Process for Data Mining. This methodology consists of the following phases: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation and Deployment. During these phases, multiple data-quality techniques were applied to improve the reliability of the real-time data. The developed model presented a significant improvement in identifying the drilling troubles in advance, compared to the current practice. Parameters such as hook-load and bit-depth, were studied. Actual data from several oil fields were used to develop and validate this smart model. This model provided the drilling engineers and operation crew with bigger window to mitigate the situation and resolve it, prevent the occurrence of several drilling troubles, result in big time and cost savings. In addition to the time and cost savings, CRISP-DM provided the artificial intelligent experts and the drilling domain experts with a framework to exchange knowledge and sharply increase the synergy between the two domains, which lead to a common and clear understanding, and long-term successful drilling and AI teams collaboration. The novelty of this paper is the introduction of data-mining CRIPS methodology for the first time in the prediction of drilling troubles. It enabled the development of a successful artificial intelligence model that outperformed other drilling troubles prediction practices.

The Wheatstone Project is an LNG development located in Western Australia, incorporating the Chevron Australia operated Wheatstone and Iago fields and third-party gas fields. Production commenced in mid-2017. The start-up of the Wheatstone and Iago fields was a unique opportunity to acquire reservoir surveillance information that was able to provide valuable reservoir insights. A key component of the analysis was the observation of pressure interference between wells from the initial well clean-ups. The design of the well clean-up sequence, discussed in a previous paper ( Flett & Connell, 2019 ) was influenced by operational guidelines and the application of Ensemble Variance Analysis to determine an optimised start-up strategy for interference testing with the objective of reducing subsurface uncertainties. The well clean-up sequence was executed safely and achieved the reservoir surveillance and operational objectives of the start-up program. Flexibility in the optimised well clean-up sequence allowed changes to the start-up strategy in response to changing operating conditions, without impacting the reservoir surveillance objectives. High quality pressure interference data was acquired, enabling clear determination of zonal reservoir connectivity within the Wheatstone and Iago reservoirs. Interpretation of pressure interference results with reservoir models, incorporating Ensemble Variance Analysis led to a change in approach for initial history matching and revision of static and dynamic model development for Wheatstone and Iago fields.

The upstream E&P industry encompasses diverse range of activities. The core activities may be broadly classified as G&G, Drilling, Production and Transportation and non-core activities supporting efficient execution of core activities and the business as a whole may be classified as Finance, Contracts and Purchase Management, HRM and Engineering services. E&P industry is one of the earliest adopters of digital technologies in its operations to efficiently transform complex reservoirs into revenues. Oil India Limited (OIL), the 2 nd largest national E&P Company of India too adopted digital technology in its G&G activities encompassing Seismic data acquisition, processing, interpretation and logging in 1970s. It was followed by use of high end workstations for reservoir studies & modelling in 80's. Over the years, OIL deployed number of digital interventions in both core and non-core activities. However, like other E&P companies, induction of digital technology is slow in core activities like Drilling and Production. As far as non-core activities are concerned, advanced digitisation methodology adopted in the area helped OIL in enhancing efficiency and ease of data access in B2B, B2C relationship. Crude oil and Natural Gas price volatility demands that E&P organizations to be more agile and competitive. Thus there is need of collaborative workplace with real time data analysis and efficient decision making facility. As a solution, number of intelligent IT technologies in the form of IoT, Data Analytics, Machine learning, Artificial Intelligence, Augmented Reality etc. are emerging at an affordable cost. Adopting these technologies in a holistic way integrating all core and non-core activities of an E&P industry can fulfil the need of above desired solution enhancing productivity, flexibility, reliability and RoI. Believing "Holistic Digital Transformation" is the success mantra to become more agile and competitive, OIL has embarked in the process of implementing new digital technologies integrating all its core and non-core activities. The paper describes OIL's methodology towards holistic digital transformation.

Big data has become a major topic in many industries. Most recently, the oil and gas industry adopted a special interest in data science as a result of the increasing availability of public domains and commercial databases. Utilizing and processing such data can help in making better future decisions. The aim of this work is to provide an example and demonstrate methodologies on how to collect and utilize big data to help in making better future decisions in the oils and gas industry. After reading a good number of papers and books about the applications of data analysis in the oil and gas industry, in addition to other industries, and given that data analysis is the area of expertise of the authors, this paper was written to demonstrate real examples of data processing and validation workflows. This work is intended to cover the gaps in the literature were many of the publications only discuss the importance of data-driven analytics. This paper provides an overview of the diverse and bulk data generating sources in the oil and gas industry, starting from the exploration phase to the end of the lifecycle of the well. It provides an example of utilizing a public domain database (FracFocus) and demonstrates a step by step workflow on how to collect and process the data based on the objective of the analytics. Two real examples of descriptive and predictive analytics are also demonstrated in this paper to show the power of having a diverse and multiple resources databases. A framework of data validation and preparation is also shown to illustrate data quality checks combined with best practices of data cleansing and outlier detection methodologies. This paper provides a clear methodology on how to successfully apply data analysis which can serve as a guide for some future data analysis applications in the oil and gas industry.

Sampling While Drilling has been successful in recent times covering numerous applications including difficult boreholes, horizontal wells, influencing drill stem test plans, cost savings in marginal fields, high sample volume collection, aid in quantifying non-hydrocarbon content for facilities design and deployment in carbonate under total losses with pressurized mud cap drilling conditions. This case study discusses one more application, which is in weak unconsolidated sands of a field located in Tatau, Sarawak, Malaysia. The principal objective of the sampling-while-drilling run discussed in this paper was to collect representative water samples from an aquifer, the laboratory analysis of which would yield invaluable information about compatibility for future water injection. The secondary objective was to collect low contamination single-phase oil samples if the well penetrated hydrocarbon reservoir layers at virgin pressure. Determining fluid gradient was an inherent requirement as well. This paper describes the challenges, best practices and learnings following the deployment of this technology in a deviated infill well in a mature oil field with sanding history and multiple layers of poorly consolidated sandstones with uncertainties on the pore pressure, due to production from the field and adjacent fault blocks that might have a certain level of connectivity.

The oil & gas industry is catching up to automation of traditional workflows practiced in the industry and implementation of artificial intelligence to fasten repetitive tasks. This is driven by the need to automate low-cognitive tasks enabling engineers to spend more time on high-cognitive components of the existing workflows, thus leading up to smarter decisions. This has been made possible by the recent developments and adoption of various analytics and machine learning tools. Well intervention and workover are a routine and important exercise undertaken in the oil and gas industry where the objective is to identify the sick wells and diagnose the right intervention and workover to improve the production. A typical well intervention and workover candidates study includes: Identifying the underperforming wells, Diagnosing these wells and identifying the right workover/ intervention opportunities Creating a ranking of the opportunities using a standard approach. Forecasting the gain after workover/intervention Running economic analysis to identify the candidate based on opportunity's profitability Ujung Pangkah Oil and Gas Field is an offshore field located in Indonesia. The reservoir is a multi-layered carbonate oil and gas reservoir, being produced mostly through horizontal wells. An intelligent solution termed as SWORDS was developed for the Ujung Pangkah field that enables the engineers to be permanently aware of the intervention and workover opportunities. The SWORDS solution is driven by 'Automation & Analytics', where the ranking of the opportunities has been driven by a multi-criteria decision making process leveraging the Petroleum Engineering techniques practiced over decades.

The 2015 oil price downturn compounded by future uncertainties and volatility in the industry have resulted in significant transformation in many oil & gas companies towards identifying and removing inefficiencies and maximising the lifecycle value of the hydrocarbon assets. The need to take proactive action in enhancing the business workflows to improve efficiencies through process simplification, innovative collaboration models and cost reduction efforts. In the low oil price environment, we need to be more cash conscious, focusing mindset towards value & objective driven activities, while rethinking the commercial and contractual strategies. This paper will briefly touch upon some of the process improvements at industry level in Malaysia and its key principles and value impacts, focusing mainly on Integrated Asset Development & Management (IADM) throughout field/asset lifecycle from exploration stage to decommissioning and abandonment stage. In addition, this paper will also share examples of innovative solution of resources management towards successful development plan formulation and asset management, that serve as a platform for putting together various elements of ideas and concepts, best practices and lessons learnt, techno-commercial & data-driven initiatives, alternative industry standard approaches, and enabling technologies for IADM.

In an oil and gas project life cycle, commissioning is notably the moment of truth where the engineered, procured and constructed facilities are verified functioning for the first time. Inability to recognize a project's Commissioning and Start-Up (CSU) unique requirements would increase the risk of project failure. The risk could be mitigated by adopting the right mindset–begin with end in mind. This paper outlines the application of project management processes associated with commissioning discipline. A multinational operating company undertook a complex mega scale project that aimed to develop an integrated gas field and Enhanced Oil Recovery (EOR) in offshore Sarawak, Malaysia. The project, executed by multiple Package Contractors, is composed of a new central processing platform (CPP), 2 new wellhead platforms, 6 new pipelines, 1 submarine cable, 9 brownfield platforms, 16 new wells and 4 workover wells. Commissioning Team was mobilized as early as Front-End Engineering Design (FEED) and adopted Systemization to decompose the project complexity into manageable constituents. The CSU Philosophy was designed to formulate the Integrated CSU (ICSU) Strategy that systematically drives the construction completion and synergizes the efforts. Without the strategy, each package would have been focusing in delivering individual objectives that could have compromised the chance of overall project success. However, the timely deployment of it has realigned the execution strategies, noting that offshore project environment is largely dependent on marine vessels arrangement. The strategy managed also to break the silo mentality and encouraged collaboration and communication among the packages and Operations even before the start of the main offshore campaign. The teamwork, of 1200 manpower and 25 marine vessels at peak, was continued offshore and has materialized the introduction of hydrocarbon to CPP 40 days ahead of schedule. Subsequently, the first gas achievement was accelerated by two months ahead of schedule. Additionally, the risk of commercial exposure due to standby of marine vessels and resources caused by clashing of activities, was successfully mitigated. The experience and lessons learnt from the project can benefit others to undertake similar projects safely and successfully in terms of strategizing, planning and execution.

Recent years have witnessed advancements in the oil and gas (O&G) industry related to the 4th Industrial Revolution and advanced analytics. O&G data has been a key that fuels these advancements. Proper management of O&G data could unleash the full potential of analytics for the O&G industry. Tackling this challenge may involve time consuming manual steps that may introduce inaccuracies along the way. In this work we aim to improve the efficiency of O&G data management in three aspects. First, by simplifying the tagging process of O&G files and largely reducing the manual work involved. Second, by enhancing the searchability of O&G files. Third, by reducing the overhead of data redundancy. Our approach utilizes Natural Language Processing (NLP) techniques and Fuzzy theory concepts to produce three elements. The first element is a metadata extractor, which can automatically extract search keywords from O&G files. The second element is an algorithm we built to tag O&G files. This algorithm can be trained against predefined business categories and label a target file with the right category. It can also produce a (fuzzy) degree of membership of the file to other categories. This algorithm can be used to automate tagging of legacy historical files. The third element is a utility that we built to enable data managers find similar and duplicated files across multiple O&G file repositories. It also combines the first two elements to simplify and automate tagging of historical, untagged, files and migrate them to a central repository. Our approach and algorithms do not use any metadata defined manually by users. Rather, they work entirely on textual content inside files to tag them, discover similarities and extract their metadata. We tested our approach on an O&G dataset of text documents related to drilling, exploration and production. This dataset comes in different formats (reports, spreadsheets and presentations) and is distributed over multiple repositories. The test included two scenarios: document tagging and discovering duplicated files. The results show that our tagging algorithm was able to achieve over 95% tagging accuracy. Automated file tagging with such accuracy can significantly reduce the steps to classify O&G files. This can be useful when migrating legacy data to a central repository. The test also resulted in discovering all duplicated files with a similarity score between 95% and 100%. This enables data managers to migrate the correct version of duplicated files to a central repository and thus achieve data accuracy, reduce the search effort, and also reduce disk space required. Our work introduces a unique approach to optimizing the efficiency of O&G data management and automate key steps such as document tagging. In addition, we believe that the tagging algorithm we built is unique in the O&G industry.

PT Pertamina Hulu Indonesia ("PHI") was founded in December 28 th , 2015 as a subsidiary of PT Pertamina (Persero) ("Pertamina"). PHI was established as operation holding company to operate, manage, and conduct upstream activities in working areas, which were handed over to Pertamina by Government of Indonesia ("GoI"). The corporate objectives of PHI are to maintain production, to increase reserves, to conduct exploration activities and to assist/provide guidance in terms of HSSE policies of the working area. Recently, PHI has three subsidiaries: PT Pertamina Hulu Mahakam ("PHM"), PT Pertamina Hulu Sanga Sanga ("PHSS"), and PT Pertamina Hulu East Kalimantan ("PHKT"). Each subsidiary requires many approaches to restrain high natural declined rate related to drilling, workover, and well services activities. Consequently, Pertamina as the new Operator had to immediately conduct such activities even prior to effective date of its operatorship. Pertamina has invested in PHI through its first subsidiary since 2017 through drilling 15 wells, 12 workover, and hundred of well services activities. In addition, 7 new Plan of Development(s) ("POD"s) have been agreed for 180 new drilling jobs in 2018 onwards to support production target. Meanwhile for other subsidiaries, Pertamina immediately conducted upstream activities consist of 2 new drilling jobs, 9 workover & 70 well services for its second subsidiary, and 10 workover & 59 well services for its third subsidiary, right after the blocks were handed over. To ensure drilling and well intervention activities conducted properly, many material and services contracts must be prepared and available on time prior to program started, such as Drilling Rig Services, Drilling Fluid Services, Cementing Services, Electric Logging Services, Wellhead Services, Coiled Tubing Unit Services, et cetera. It has to be started from the beginning of and completed within the transition period. However, throughout transition period, PHI was dealing with some concerns due to many parties involved, especially regarding information restriction and confidentiality included into legal issue. In addition, PHI had also limited time and drilling personnel resources to prepare the contracts required to execute drilling and well intervention program. To encounter challenges above, the first thing to be prepared was Transfer Agreement ("TA"), and both parties (PHI and former Operator) to align rights and responsibilities of each party must sign it. PHI was succesfull in providing all required contracts for the continuation of transition and operation activities at PHI subsidiaries. Over the transition period, PHI already providing the procurement contracts directly related to drilling and well intervention activities, as follows: 158 contracts from former Operators and 60 new procurements for the new Operators. This paper will describe the successful contract strategy implementation of three subsidiaries in PHI which proven to be an efficient example of working area transition period in term of contracts.

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. 2 nd 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.

Optimization of permanent liner completions in the North Kuwait Jurassic Gas (NKJG) reservoirs has been an ongoing challenge progressed on a steep learning curve within the last decade. Various completion options are field-tested in determining the optimal completion hardware and activation methodology. The asset's objectives have been multi-dimensional: preserve natural fractures, minimize formation damage, segregate, stimulate and activate optimally, while installing permanent completions hardware efficiently, which can withstand 15,000-psi differential pressure at high temperature and sour gas environment and sustain production for the well life of over 20 years. NKJG faces the enormous task of increasing the hydrocarbon production potential by over 200% within a short time period. The reservoirs are high-pressured and high-temperature (HTHP) gas condensate assets with tight matrix properties (i.e. <0.1 mD permeability), in variation with naturally fractured sections within flow-zones separated into eight segments. Preserving the natural fractures, removal of near wellbore damage and segregating flow-zones based on lithology and critical reservoir properties are important especially in peripheral subsurface locations, where the realization of full reservoir potential is not only essential for production success, but also required for appraisal of boundary conditions. For realizing these objectives, the asset custom-designed a multi-stage completion system with hydro-mechanical liner hanger packer, open-hole packers, hydraulic anchor and multiple frac ports set and activated as a drop-ball system. Due to the high completion loads, differential body and packer rating are manufactured to 15,000 psi using corrosion resistant alloy throughout, with the PBR and seal-bore assembly designed to withstand differential pressures and contraction during multiple fracturing events. Custom-designed multi-stage completion assembly (MSC-HP) was successfully installed, sequentially hydraulic-fracced and commingle-tested on flowback. Customized operational guidelines were established including a pre-set success criterion, openhole and caliper log sequences, tie-back cementation and subsequent clean out trips, followed by hole conditioning and reamer runs to compute the final drag and friction forces. Differential sticking risks were mitigated by avoiding the "pressure ramps" exacerbated by differential depletion evident in the area. Reservoir was segmented in three distinct intervals to maximize flow potential. As a result, the asset's objectives were successfully met, with the additional benefits of proving multiple zone activation, each with a complicated sequence of operational events, performed sequentially in four days. This paper documents the project cycle from successful planning and design, to installation and execution phases of the MSC-HP in peripheral deep NKJG asset. Key learnings and critical factors, which led to the successful well results in spite of less favorable subsurface location are summarized. Added complications due to the severe NKJG specs will be discussed as the number of global analogues is scarce leading to limited opportunities for the industry to learn from in unconventional/conventional mix layered carbonates.

The Australia Pacific LNG (APLNG) Downstream Project comprised construction of a two-train LNG plant, two 160,000 m 3 LNG storage tanks, a LNG loading jetty, and associated infrastructure on Curtis Island, near Gladstone, Queensland. The facility utilises ConocoPhillips’ proprietary Optimized Cascade ® process to liquefy natural gas. Project planning began in 2008 and construction commenced in 2011. LNG production from Train 1 began in December 2015 and Train 2 came on line in October 2016. In August 2017, the final 90-day two-train lenders test was successfully concluded and included an operational component in which the LNG Facility operated at ten per cent above nameplate capacity for the 90-day period. This successful outcome was achieved through collaboration, integration and robust execution plans by the APLNG Operations, APLNG Project, ConocoPhillips LNG Technology and Licensing and Commissioning and Start-up work teams. In an effective strategy to support the drive to APLNG first cargo, the combined teams formed a fully Integrated Completions Team in 2015. This team worked together enabling rapid development of the operations workforce capability and resulted in both trains achieving performance tests at first attempt. The APLNG Project operability assurance and operations readiness program commenced with a collaborative workshop, attended by Operations, Projects and Commissioning and Start-up representatives. A focus on high collaboration and integration between the teams backed by ConocoPhillips’ Operability Assurance (OA) and Operations Readiness (OR) principles identified 370 critical business deliverables. Learnings were leveraged from across ConocoPhillips assets (including Darwin LNG) as they pertained to readiness best practice. APLNG Readiness Assurance guidance was established to create specific functional readiness trackers to measure every action supporting the 370 deliverables. A simple and effective tool was developed and supported by robust monthly review forums where each action was tracked and rolled up to S-Curves. These deliverables translated to over 7,000 unique line items tracked over the entirety of the readiness implementation. This work was leveraged by the Integrated Completions Team which implemented robust lessons learned from Train 1 to realize immediate results, delivering a 33% reduction in the Train 2 start-up schedule. The combined efforts of the teams delivered two highly operational trains within the 2016 calendar year resulting in the production of additional cargoes. The successful execution and implementation of OA/OR principles combined with strong integration of APLNG Operations into the APLNG Project phase laid the foundation for exceptional first year operational and production performance. This meant the APLNG Operations Team moved from a newly formed team to a high functioning and critically evolving team in support of the APLNG Downstream LNG Facility.

K field is a faulted anticline structure lying in a turbidite environmental setting, which consists of two main sand bodies of 50-100ft gross thickness. Two main challenges during development stages were, 1). The narrow thickness of the fault block requiring accurate landing, well placement and characterization. 2). The low vertical permeability inside the sand which requires the straddling and precision of horizontal placement relative to reservoir boundary. Geosteering was proposed to mitigate those challenges, which is then translated into a directional drilling plan. Hybrid LWD combination of Seismic, Reservoir Mapping, RT-Image and Formation Pressure While Drilling technology were used overcome those objectives and challenges. Seismic was used to update target uncertainty in both depth and lateral coordinates, hence accurate landing inside the target fault block was the main driver. Reservoir Mapping Technology and borehole images were used to update the presence of fault and plan for an accurate placement of the horizontal section. Pressure While Drilling was used to update the reservoir pressure and fault/ connectivity between fault/compartments. Post job subsurface modeling was updated using those measurement for accurate interpretation, which was used for future field development plan. The drilling workflow was extensively discussed among the stakeholders to make sure it was fit for purpose and could achieve the objectives. Horizontal well landing procedures using Seismic While Drilling technology helped the well penetrate into fault block A at 100m before fault edge. Reservoir Mapping While Drilling technology enabled successful Geosteering inside the desired target zone. Another important application regarding the Reservoir Mapping Technology is the capability of resolving the internal sedimentary bedding feature (higher dip feature) and the delineating of multiple faults including sub seismic fault block B, which helped the team define well TD at the desired fault block position. An integrated interpretation between Reservoir Mapping While Drilling, High Resolution Images and Formation Pressure While Drilling to detect pressure continuity between one block to the other proved to be very helpful for production management and completion optimization. At the end, two horizontal wells were successfully drilled in the desired fault block. Everything worked, ie the technology, the people and the process, resulting in an accurate and well controlled execution of a complex and high-profile project. The novel approach was successfully demonstrated to ensure well objectives are achieved in an integrated manner. The flawless execution allowed the team to avpid drilling any side tracks which would have been costly.

As Malaysia’s first tension leg platform, the Shell Malikai project, represents an unconventional approach towards deepwater operation in this region. In a field embedded characterized by reservoir drawdown from adjacent production wells, the lowest cementing margin is 0.65 ppg. Annular gaps between casings of as tight as 0.53 in each side further elevates the equivalent circulating density (ECD). Cementing software simulation predicts risk of heavy losses during cement placement and subsequently lack of isolation between multiple hydrocarbon-bearing zones. The loss of zonal isolation would mean crossflow between the reservoir. At worst case, some of the water injector wells may be abandoned due to inability to inject into the target reservoir and uncertainties of injection efficiency. This represents a significant loss of capital investment. A two-pronged solution has been developed to secure the long-term well integrity of the deepwater project. Implementation involved front-end design, modelling, planning, and execution. Two-stage cementing is a technique by which selected intervals along the casing can be cemented in separate stages. It reduces the risk of losses due to long column of cement slurry exerting high hydrostatic head towards the weak formation. In 11 3/4in liner with tight annular gap, the risk of taking losses is high. Therefore, two-stage cementing was employed, combined with specialized blended lightweight 11.5-ppg cement. First-stage cement will provide good liner shoe strength for drilling ahead, and second-stage cement will provide zonal isolation for two hydrocarbon zones near the top of the liner. For 9 5/8in liner, due to the presence of a pressure ramp at the top of the section and weak formation at the bottom, managed pressure cementing (MPC) was the chosen approach to mitigate the risk of losses. MPC is a technique that enables cementation to be conducted in a hydrostatically underbalanced condition where surface backpressure (SBP) is applied to maintain the bottomhole pressure between the highest pore pressure and the lowest fracture pressure of the well. The combination of MPC and two-stage cementing, together with other existing best practices, formed an integrated solution in narrow margin cementing. This has resulted in flawless cementation for two water injector wells. No losses were observed during cement displacement, there was no gas migration, and the liner top packer was successfully set, and pressure tested in MPC mode. A subsequent cement log confirmed the top of cement requirement was fulfilled. The paper will further explain on how this unconventional technique were planned and executed.

In complex situations production optimisation often differs from plan to reality. Ideally a set of known factors are used to determine the optimal course of action for a production well. However, in reality many factors remain unknown and of those that are, many are only known within a range of uncertainty. Uncertainty is persistent; whether in the form of failed instrumentation, erroneous metering or production reconciliation to multiple reservoirs in commingled completions. Further, well optimisation is always governed by economics and operational constraints. Such constraints limit well surveillance activities and compound uncertainty. These challenges united when a large bore deviated depletion drive gas well on a small unmanned offshore platform in the Otway Basin began to exhibit unexpected production decline. The large bore gas well with commingled reservoir completions was diagnosed as exhibiting liquid loading behavior. The intervention objective was to isolate the probable formation water source and restore water free gas production. A production log was required to confirm water was present and identify the source from three groups of completed intervals, each separated from one another using packers and mechanical sliding side doors. After risk assessments conducted during the intervention an active decision was taken to abort the work and not isolate the water source in favour of continuing cycled production to maximise gas recovery. Introducing an unknown, production logging identified that one of the three completed reservoir intervals was isolated by a closed sliding side door, previously believed to be open, presenting an incremental production opportunity. A follow-up intervention retained an objective of isolating the water source, with the additional objective of accessing the isolated reservoir interval. Detailed planning and uncertainty analysis was conducted ahead of the campaign with a key risk being the range of pressure possibly present within this target interval and the resultant wellbore cross-flow immediately after accessing it. Whilst the second intervention experienced mechanical failure, the ensuing pragmatic decisions that were taken "on the fly" ultimately resulted in a successful production outcome. The water source was isolated and incremental rate and reserves were achieved through perforation of blast joints opposite the target interval. This paper presents the workflows, tools & interventions used to diagnose production decline and optimise production from this challenging well. It is a case study in production surveillance utilising limited data, decision tree analysis and contingency planning for interventions performed with significant operational limitations. It includes the use of slickline production logging, tubing plugs, and electric wireline perforating in a strong cross-flow wellbore environment. This paper will be of interest to operators of unmanned platforms in hostile environments, commingled completions or wells with compromised production data. By integrating the learnings presented, engineers will get a head start when tackling similar uncertainties with their own challenging production optimisation activities.