Objectives/Scope (25 - 50) PDO is in the process of transforming its well and urban planning by adopting digital technologies and Artificial Intelligence (AI) to improve organizational efficiency and maximize business value through faster quality decision. In 2020, PDO collaborated with a third-party contractor to provide a novel solution to an industry-wide problem: "how to effectively plan 100's of wells in a congested brownfield setting?". Business Transformation This paper describes an innovative AI-assisted well planning method that is a game-changer for well planning in mature fields, providing efficiency in urban and well trajectory planning. It was applied in one of PDO's most congested fields with a targeted infill of 43m well spacing. The novel well planning method automatically designs and optimizes well trajectories for 100-200 new wells while considering surface, subsurface and well design constraints. Existing manual workflows in the industry are extremely time consuming and sequential (multiple man-months of work) - particularly for fields with a congested subsurface (350+ existing wells in this case) and surface (limited options for new well pads). These conventional and sequential ways of working are therefore likely to leave value on the table because it is difficult to find 100+ feasible well trajectories, and optimize the development in an efficient manner. The implemented workflow has the potential to enable step change in improvements in time and value for brownfield well and urban planning for all future PDO developments. Innovation The innovative AI assisted workflow, an industry first for an infill development of this size, evaluates, generates and optimizes from thousands of drillable trajectories to an optimized set for the field development plan (based on ranked value drivers, in this case, competitive value, cost and UR). The workflow provides a range of drillable trajectories with multi-scenario targets and surface locations, allowing ranking, selection and optimization to be driven by selected metrics (well length, landing point and/or surface locations). The approach leads to a step change reduction in cycle time for well and urban planning in a complex brownfield with 100-200 infill targets, from many months to just a few weeks. It provides potential game-changing digital solutions to the industry, enabling improved performance, much shorter cycle times and robust, unbiased well plans. The real footprint and innovation from this AI-assisted workflow is the use of state-of-the-art AI to enhance team collaboration and integration, supporting much faster and higher quality field development decisions. Application of Technology This paper describes a novel solution to integrated well planning. This is a tangible example of real digital transformation of a complex, integrated and multi-disciplinary problem (geologists, well engineers, geomatics, concept engineers and reservoir engineers), and only one of very few applied use cases in the industry. This application also gives an example of "augmented intelligence", i.e. how AI can be used to truly support integrated project teams, while the teams remain fully in control of the ultimate decisions. The success of this approach leans on the integrated teamwork across multiple technical disciplines, not only involving PDO's resources, but also WhiteSpace Energy as a 3rd party service provider. The enhanced collaboration allowed all parties to highlight their constraints in an integrated way from the start, strengthening the technical discussion between disciplines and learning from each constraint impact and dependencies. (e.g. dog leg severity). In summary, the change in process flow moving from a sequential well planning and urban planning method to an iterative and fast AI solution – including all technical considerations from beginning represented for PDO an added value of over 6 months of direct cycle time HC acceleration.
The South Oman clusters A and B have reclassified their Deep-Water Disposal wells (DWD) into water injection (WI) wells. This is a novel concept where the excess treated water will be used in the plantation of additional reed beds (Cluster A) and the farming of palm trees (Cluster B), as well as act as pressure support for nearby fields. This will help solve multiple issues at different levels namely helping the business achieve its objective of sustained oil production, helping local communities with employment and helping the organization care for the environment by reducing carbon footprints. This reclassification covers a huge water volume in Field-A and Field-B where 60,000 m3/day and 40,000 m3/day will be injected respectively in the aquifer. The remaining total excess volume of approx. 200,000m3/d will be used for reed beds and Million Date Palm trees Project. The approach followed for the reclassification and routing of water will: Safeguard the field value (oil reserves) by optimum water injectionMaintain the cap-rock integrity by reduced water injection into the aquifer.Reduce GHG intensity by ±50% as a result of (i) reduced power consumption to run the DWD pumps and (ii) the plantation of trees (reed beds and palm trees).Generate ICV (in-country value) opportunities in the area of operations for the local community to use the excess water at surface for various projects.Figure 1DWD Reclassification benefits Multiple teams (subsurface. Surface, operations), interfaces and systems have been associated to reflect the re-classification project. This was done through collaboration of different teams and sections (i.e. EC, EDM, SAP, Nibras, OFM, etc). Water injection targets and several KPIs have been incorporated in various dashboards for monitoring and compliance purposes. Figure 2Teams Integration and interfaces It offers not only a significant boost to the sustainability of the business, but also pursues PDO's Water Management Strategy to reduce Disposal to Zero by no later than the year 2030 This paper will discuss how the project was managed, explain the evaluation done to understand the extent of the pressure support in nearby fields from DWD and the required disposal rate to maintain the desired pressures. Hence, reclassifying that part of deep-water disposal volume to water injection (WI) which requires a totally different water flood management system to be built around it.
PDO is in the process of transforming its well and urban planning by adopting digital technologies and Artificial Intelligence (AI) to improve organizational efficiency and maximize business value through faster quality decision. In 2020, PDO collaborated with a third-party contractor to provide a novel solution to an industry-wide problem: "how to effectively plan 100's of wells in a congested brownfield setting?". This paper describes an innovative AI-assisted well planning method that is a game-changer for well planning in mature fields, providing efficiency in urban and well trajectory planning. It was applied in one of PDO's most congested fields with a targeted infill of 43m well spacing. The novel well planning method automatically designs and optimizes well trajectories for 100-200 new wells while considering surface, subsurface and well design constraints. Existing manual workflows in the industry are extremely time consuming and sequential (multiple man-months of work) - particularly for fields with a congested subsurface (350+ existing wells in this case) and surface (limited options for new well pads). These conventional and sequential ways of working are therefore likely to leave value on the table because it is difficult to find 100+ feasible well trajectories, and optimize the development in an efficient manner. The implemented workflow has the potential to enable step change in improvements in time and value for brownfield well and urban planning for all future PDO developments. The innovative AI assisted workflow, an industry first for an infill development of this size, evaluates, generates and optimizes from thousands of drillable trajectories to an optimized set for the field development plan (based on ranked value drivers, in this case, competitive value, cost and UR). The workflow provides a range of drillable trajectories with multi-scenario targets and surface locations, allowing ranking, selection and optimization to be driven by selected metrics (well length, landing point and/or surface locations). The approach leads to a step change reduction in cycle time for well and urban planning in a complex brownfield with 100-200 infill targets, from many months to just a few weeks. It provides potential game-changing digital solutions to the industry, enabling improved performance, much shorter cycle times and robust, unbiased well plans. The real footprint and innovation from this AI-assisted workflow is the use of state-of-the-art AI to enhance team collaboration and integration, supporting much faster and higher quality field development decisions. This paper describes a novel solution to integrated well planning. This is a tangible example of real digital transformation of a complex, integrated and multi-disciplinary problem (geologists, well engineers, geomatics, concept engineers and reservoir engineers), and only one of very few applied use cases in the industry. This application also gives an example of "augmented intelligence", i.e. how AI can be used to truly support integrated project teams, while the teams remain fully in control of the ultimate decisions. The success of this approach leans on the integrated teamwork across multiple technical disciplines, not only involving PDO's resources, but also WhiteSpace Energy as a 3rd party service provider. The enhanced collaboration allowed all parties to highlight their constraints in an integrated way from the start, strengthening the technical discussion between disciplines and learning from each constraint impact and dependencies. (e.g. dog leg severity). In summary, the change in process flow moving from a sequential well planning and urban planning method to an iterative and fast AI solution – including all technical considerations from beginning represented for PDO an added value of over 6 months of direct cycle time HC acceleration.
Since the mid 1990's a number of sour oil fields, comprising carbonate reservoirs and silicilyte reservoirs have been discovered in the South of Oman. The main common feature of all these fields, which stretch over an area of 150x50km, is the stratigraphic nature of the trap, whereby the reservoir and source rock is entirely encased by salt. The crude is light, sour and often heavily undersaturated. Despite significant depths of 3000-5000m and initial reservoir pressure gradients often far above the hydrostatic gradient, the primary depletion recovery is in general low, in the range of 10-15%. Wells generally quit from lift die-out at a fairly high production rate once the reservoir reach their bottom hole pressure limit, and no artificial lift method could successfully be implemented because of the high pressure, high sour and high GOR environment. This resulted in the need for secondary/tertiary development to access the significant oil volumes left in the fields. Plans towards the implementation of Enhanced Oil Recovery (EOR) by the mean of Miscible Gas Injection (MGI) were put in place covering most fields in the cluster. A structured implementation staircase was followed, gradually increasing the confidence in the recovery process through lab tests and field trials, and maturing field development projects through the opportunity realization steps. The commissioning of the Station-H and the implementation of the AN MGI 3A project mark the realization of the first tranche of MGI floods in Oman; it includes three projects:A full-field implementation in the Z-field, which started in April 2012 and is now injecting at 80% of the capacity into six injectors,A pilot flood in the S-field (S-Miniflood), which started in May 2015, injecting through 3 crestal wells into the pre-existing gas cap at a distance of 2000-2500m from the producer.A pilot project of two five-spot patterns in the AN field (3A), which started injecting in September 2015 At present injection has been going on for over 3 years at the full field level in Z-field, which is now showing a clear positive response. The reservoir pressure has risen above the Minimum Miscibility Pressure (MMP) of 380bar and excellent FTHP is observed (above 150bar) and producers that had previously reached lift die-out have been reopened. The asset's liquid production has increased by 3 fold and contributes to more than 15% of Oman's production. This project is the world's largest Enhanced Oil Recovery (EOR) with Sour Miscible Gas Injection (MGI) integrating oil and gas field developments. Sour gas is processed through a state-of-the-art processing facility for sweetening and re-injecting gas under MGI to increase oil recovery up to 50%, (i.e. 6 fold increase over primary RF). The two pilots (S-Miniflood and AN 3A) are also under heavy WRFM scrutiny for optimal flood management, and monitoring of KPI. They are expected to run for circa 4 yrs prior to unlocking the implementation at the full field scale. These projects provide the infrastructure for long term development of the area and a number of follow-on projects, which will make use of the existing facilities or lead to commissioning of larger facilities.
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