Drilling wells with minimum risk and optimizing well placement with the least possible cost are key goals that companies strive to achieve. The major contributor to the successful execution of the well is the quality of the drilling program. Well design is a complex process, which requires full collaboration of multiple domain roles & expertise working together to integrate various well-planning data. Many design challenges will be encountered, such as risk assessments, domain-specific workflows, geological concerns, technology selections, cost & time estimation, environmental and safety concerns. Design process efficiency depends on effective communication between parties, quickly adapting to any changes, reducing the number of changes, and reducing complicated & manual processes. Current existing workflow and tools are not promoting an excellent collaborative environment among the different roles involved. Engineers utilize multiple engineering applications, which involved many manual data transfers and inputs. The different party is still working in a silo and sharing the design via email or other manual data transfer. Any changes to the design cause manual rework, leading to inconsistency, incoherency, slow decision & optimization process, and failure to identify all potential risks, increasing the well planning time. The new digital planning solution based on cloud technology allows the design team to maximize the results by giving them access to all the data and science they need in a single, standard system. It's a radical new way of working that gives engineers quicker and better-quality drilling programs by automating repetitive tasks and validation workflows to ensure the entire plan is coherent. This new planning solution allows multiple roles & domain collaboration to break down silos, increase team productivity through tasks assignment, and share all data. An automated trajectory design changes the way engineers design trajectory from manually connecting the path from a surface location to the target reservoir location to automatically calculate & propose multiple options with various KPIs allowing the engineer to select the best trajectory option. The system reinforces drilling program quality through auto engineering analysis, which provides quick feedback for any design changes and provides an integrated workflow from the trajectory design to operational activity planning and AFE. The automation of repetitive tasks, such as multiple manual inputs, frees domain experts to have more time to focus on creating new engineering insights while still maintaining design traceability to review updates over the life of the projects and see how the design changes have optimized the drilling program. This new solution solves some of the significant challenges in the current well-planning workflow.
Digital well construction tools are becoming more widely considered today for well design planning, enabling automated engineering and simultaneous team collaboration under a single solution. This paper shows the results of using a digital well construction planning solution during a project’s conceptual planning stage. This method shortens the time needed to estimate the well times and risk profile for a drilling campaign by applying smart engines to quickly and accurately perform critical offset analysis for defined well types that is required for project sanction. With this solution, the Offset Well Analysis (OWA) process is done automatically based on the location of the planned well, trajectory and well architecture. Various information and reports (both subsurface and surface data) from neighboring wells is stored in cloud solutions, enabling ease of access and data reliability for both large or smaller scale data storage. The software selects the most relevant offset wells, displays the risk analysis and generates the stick chart. For a conceptual design, the risk levels can be manually set higher due to potential unknowns in surface and subsurface risks which can later be refined. Quick validation of the well design allows the engineer to design a conceptual drilling campaign quickly and more efficiently. The solution minimizes the time to perform probabilistic time and risk estimations. It reduces the risk of biased decision making due to manual input and design. This allows for better-informed decisions on project feasibility, alignment of stakeholders, increased design reliability as well as reducing the amount of time and resources invested in OWA. The work presented here is aimed at sharing the experience of applying a digital well construction planning solution specifically on the conceptual project stage and discuss the value it adds to the well design process.
Many operators commit to reducing their operation's carbon dioxide (CO2 emissions. According to McKinsey & Company (2020)(1), well drilling and extraction processes contribute 8% of the Scope 1 emissions in the oil and gas industry. Rig site activities generate one-third of the overall emissions footprint for the well construction process. A well construction process consists of hundreds of activities and tasks ranging from well spud to rig release. Along the way, many different types of equipment are used. To minimize emissions, we need to analyze how the power is used and how it can be saved throughout the well construction process. Selecting lower-carbon energy sources can significantly reduce Scope 1 emissions, but the transition process takes time. The operator and contractor must continually improve their operation's efficiency to reduce emissions. The emissions footprint model was developed based on CO2 emissions data and power consumption statistics for land rigs. During well planning, the engineer strives to formulate a drilling program considering the anticipated time, cost, and overall emissions objectives. Emissions volumes should be calculated based on the equipment used in each activity. The engineer compares the technologies proposed for the drilling program to determine the optimum equipment solution with the lowest overall environmental impact. The ability to forecast expected emissions for planned wells helps the engineer make technology selections for each drilling plan. With validated models, it's possible to calculate the CO2 released based on the measured drilling parameters and work to reduce it. For sustainability purposes, the engineer must consider the total emissions created by the entire process as an additional performance indicator. In this paper we describe the integration of emissions footprint modeling into the overall well-planning workflow. We developed the model by measuring actual emissions and power usage of different rig equipment during different drilling activities. This was done by using a cloud-based well-construction planning solution. The workflow was embedded into the overall well design, enabling the engineer to visualize each project's anticipated time, cost, and emission. Energy consumption was correlated using the provided drilling parameters. Therefore, the emission can be successfully predicted for different well-construction scenarios, drilling technology, and related parameters. This new workflow enables the engineer to plan with sustainability objectives and determine the best overall drilling program for each project.
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