The Digital Field initiative is transforming the daily operations on the oilfield and it is now part of PETRONAS corporate wide digital strategy. This transformation is done by onboarding multiple disciplines such as subsurface team, facilities, and operations, HSSE and Business Planning and is designed to replicates the performance of an oilfield in the computer, combining business process management and technical workflows. Digital Field has enabled the customer to execute their work collaboratively, by providing decision support system (technical workflows and business process management tools) subsequently improving their process efficiencies and optimizing their production. It is believed that by conducting a systematic review of the improvement and tracking the values that has been achieved, it will help to promote and accelerate digital adoption faster. The main objectives of the Automated Value Tracking are: To promote opportunity generation through collaborative environment. To track stages of every opportunity of the following categories of Production Optimization, Unplanned Deferment and Process Cycle Efficiencies. To quantify values associated with opportunities generated from automated workflows and current business process. To promote ownership of the actions associated with the assigned opportunity and to help to quantify on individual level contribution to the corporate goal in terms of production volume and time savings. To measures optimized number of opportunities generated against production volume associated with Production Optimization activity according to Field category and Quality of Opportunity Generated from Optimization Advisor. The process is summarized as follow: Opportunity generation: Automated opportunity generation generated through current Production Optimization Advisory framework. Integration with existing Petronas business process tools i.e. Daily Operational Tracking System, Alpha projects, Opportunity Management system, etc. Manual opportunity generation. Opportunity evaluation and analysis: Provide quantitatively confidence level of production incremental volume from automated Optimization Advisory through machine learning. Establish relationship between numbers of opportunity completed and categories versus production volume gain. Opportunity tracking and approval: Tracking the opportunity generation according to the process level. Escalating Opportunity and value recognition through business process approval. This workflow helps to improve to understand the current update of the different levels such as well, field, region and upstream with the help of integrating the value realization and allows "cards" to show information that can trigger opportunities to increase production, reduce time of decision and fast action.

This study aims to validate and track valve positions for all the zones applying recorded Distributed temperature sensing (DTS) and Distributed acoustic sensing (DAS) data interpretation in order to propose the best combination of downhole inflow control valve (ICV) openings, This is required to optimize Well X-2 multizone commingled production. Fiber DTS and DAS monitoring were relied on as an innovation against downhole conditions that has compromised the three out of four downhole dual-gauges and valve position sensors. For zonal water control purpose, ICV cycling and positioning have been attempted in 2019. The valve position tracking derived from the compromised downhole dual gauges and valve position sensors does not tally with the surface flow indication overall. Consequently, the original measurement intention of the permanently installed distributed fiber-optic which served as back-up zonal-rate calculation profiling and as potential sub-layer flow-contribution indicators is brought in as contingency zonal valve-opening tracking and guides that proved valuable for subsequent production optimization. First part of study involves interpretation of Distributed Temperature Sensing (DTS) data. Downloaded DTS data is depth matched and validated against known operating conditions like time of each cycling stage and surface well test parameters (i.e. Liquid Rate, Watercut, Tubing Head Pressure (THP), Total Gas, Gas-Oil Ratio (GOR)), etc. To establish a baseline, several DTS traces of historical operating condition during a known stable period were selected, i.e. stable flowing condition at only Zone 4 stable shut-in condition at surface with only ICV Zone 4 is opened Downhole valve-position tracking can be interpreted alternatively from induced fiber temperature activities across the valve depth with a good temperature baseline benchmarking from DTS temperature profiling. Second part of study involves interpretation of Distributed Acoustic Sensing (DAS) data. The data was acquired under single flowing condition one month post-ICV cycling. Without any changes made on the well operating conditions, the well is flowing under same condition post ICV cycling. Inflow point detection using joint interpretation of DAS and DTS, where simultaneously DAS spectral content (depth-frequency) was analysed alongside DTS traces to further discriminate between inflow and other noise sources. Through i) acoustic amplitude analysis, ii) DTS inversion, iii) noise speed and flow speed computation, composite production allocation can be derived for Well X-2. Using the alternative co-interpretations based on fiber temperature and acoustic measurement, it is found and validated that Zone 1 ICV is Closed, Zone 2, 3 and 4 are in opened position and continuously producing at any cycles. This is in conflict of zonal production control understanding initially based on the compromised downhole sensors indicating that all the zonal valves are supposedly in fully closed position. In this case-study, DTS and DAS data has been proven useful and as an innovative, alternative monitoring to determine downhole valve opening with analogue to flow contribution derivation methodology. Therefore, anytime in the future where Well X-2 valves cycling is planned to be carried out, there is now a corresponding operating procedure that is incorporated onsite real-time fiber optic DTS and/or DAS data monitoring to validate tracked valves positioning.

Well B-2 is a dual-string producers with Distributed Temperature Sensing (DTS) fiber installed along the long string (i.e. Well B-2L) across the reservoir sections. Each zone comprises of sub-layers. This system enabled the operator to continuously monitor the wellbore temperature across all the producing intervals including gas-lift monitoring, well integrity identification, zonal inflow profiling and stimulation job evaluation. This paper mainly discusses the post matrix acid stimulation job with interpreted DTS and zonal Permanent Downhole Gauge (PDG) data. Well B-2L has been selected for matrix acidizing treatment to improve the productivity due to potential formation damage, proven by the declining production over the years. Prior to the execution of the acidizing job, several conformance jobs such as injectivity test, tubing pickling were performed. This is followed by the main acid treatment and flow back. DTS & zonal PDG data were acquired throughout the operation. A transient simulator model was built incorporating all the reservoir properties including well trajectory and completion schematic to analyze the DTS profile and understand the zonal inflow profiling for each zone post treatment. A baseline temperature was acquired for the geothermal evaluation. The DTS data has been studied according to actual event schedules. Some significant findings are; i) completion accessories effect (feedthru packers) creates temperature anomalies, ii) leak points detected at top producing zone signifies cooling effect due to injected fluid. The main treatment was intended at zone 2 and 3 using nitrified acid. However, leak points at top zone caused bypassed injection into Zone 1 and 2 instead. Fiber optic DTS warmback profiles post main-treatment was analyzed to quantify the fluid intake from sub-layer in each zone. Qualitatively from the DTS-interpreted zonal profiling, the data clearly shows most of treatment fluid is being injected into Zone 1 and 2 with no intakes at Zone 3. Furthermore, warmback analysis confirmed the high intake zones from sub-layers within the main zone based on the permeability contrast. This paper will further discuss the zonal injectivity understanding for improvement from the zonal-inflow profiling evaluation by incorporating DTS, PDG and surface production data.

Over the last few years, the oil and gas industry had observed a rapid increase in deployment of fiber optic sensing for downhole monitoring. In Field B, 7 wells have been permanently completed with Distributed Temperature Sensing (DTS) fibers that extend through the reservoirs section 2009 and 2015 respectively. After more than 40 years of production history, this was the first permanent installation of fiber-optic in SX Region. Undeniably the DTS provides a new surveillance experience for Field B; multiple conventional monitoring system can be replaced with permanent fiber monitoring while also effectively minimize production deferments. This paper presents the real-life challenges of fiber optic applications in Field B, offshore Malaysia. DTS wells are located in satellite platforms which are not accessible on daily basis. While the focus is always on downhole monitoring deliverables, a large proportion of upfront deployment is to invest on the surface equipment that can be complex and costly for data acquisition continuity. As such, biggest challenges faced by Field B are essentially surface-related. Challenges encountered post DTS fiber installations in Field B includes digital oil field set-up, surface hardware replacement and maintenance, local electric room (LER) power-supply stability, data transfer protocol, continuous streaming of DTS data from offshore to onshore, reduced data resolutions, software and capability development. Over the life of the well, these challenges possess significant cost impact and most of time are not captured during the project planning and development stages. In Field B, throughout 5 years post fiber-optics installation, multiple challenges have been overcome in order to maximize value of information from the downhole monitoring. Knowing that these challenges might impact the downhole monitoring deliverables, the plan for future permanent fiber optic installation in any asset should incorporate all the possible challenges with its mitigation plans identified and set in-place. The lesson-learnt highlighted are turned into future project best practices.

In S-Field, first oil was in 1975, and the field is undergoing a redevelopment project. Integrated operations (IO) has been identified as part of the redevelopment initiative aiming at providing an asset decision support system. The S-Field operator has identified gravity-assisted simultaneous water and gas injection (GASWAG) as the suitable enhanced oil recovery (EOR) method for the field's reservoir. In implementing a digital oilfield solution addressing the GASWAG performance in S-Field, only the EOR field development plan exists as a guidance. S-Field is the first of its kind to implement EOR GASWAG. This increases the uncertainty of the agreed metrics for measurement and formulas to monitor and implement control of the effectiveness of GASWAG (sweep efficiencies and volume displacement). The scope given is to implement an EOR GASWAG-compatible digital solution that allows flexibility for the users to update their established analysis methods and that uses a web application as a basis for periodic assessment and monitoring within the asset team. The current implementation of IO at the software level has minimum flexibility to change a workflow. Any changes that are not considered during workflow development and deployment require a specialist from the development team to implement. The described system addresses the challenges in implementing digital solutions for EOR, including introducing more flexibility in adapting to changes in workflows. The EOR applications include a reservoir simulator to assist the estimation of vertical and areal sweep efficiencies and residual oil displacement in each formation; a geomodel application: to provide graphical interface of the oil, gas, and water distribution in S-Field MN reservoir model; and a data analysis application to provide classical reservoir analysis and method. To bring the applications together as digital solutions, only applications with application programming interfaces (API) are selected. This is to minimize the development effort. The analysis of EOR GASWAG can be maintained by any user through the current software. This means any changes in the analysis method can be implemented within the existing software interface without affecting the overall solutions. The changes will then be reflected in the corporate-wide implementation (web application) without the presence of a specialist and lengthy administration process. Applications with API allow extensibility that minimizes the data extraction effort and drives higher utilization time and effort that can be invested in geological models and engineering analysis. In addition, the system minimizes the change management effort because the process leverages current business processes and reduces the cost of investment by using the existing centralized powerful processing computer. Developing the solution through an analysis application that has the extensibility (API) to other third-party applications has significantly reduced the project implementation duration by half of the initial estimated effort (benchmarked with current project alike).