During drilling operations, there are two main categories of data that are generated: 1) high frequency data, which comes from rig and downhole sensors; and 2) low frequency data, such as mud reports and daily drilling reports (DDRs). Although the sensor data is delivered at a high frequency, it can suffer from a lack of context that usually comes from the low frequency reports. For example, knowing the drilling activities such as drilling ahead, back-reaming and circulating on bottom allows the correct interpretation of sensor data taken during those activities. Further, sensor data is usually minimal or non-existent during certain activities such as when the BHA is out of the hole. The DDRs are not granular enough to be useful for accurate analysis, but the combination of both low and high frequency data allow for both the granularity and context to be combined in order to properly analyze the data and optimize operations.
Since the data is derived from multiple vendors, through different sensors, connectors, and databases, manually collecting and compiling these data was historically a laborious and time-consuming process. This resulted in delayed, reactive decisions which in turn could result in incidents such as stuck pipe or increased costs associated with NPT or invisible lost time (ILT). The ultimate goal is to enable proactive or predictive decisions, which requires timely gathering, calculation, analysis, and interpretation of these data.
The digitalization of the energy sector has accelerated across all aspects of well construction operations and allowed the provision of data in real time or near real time to enable timely and effective decisions. The volume of data has also soared through an increase in data frequency, now available in millisecond rates. This provides drilling engineers with even more detailed information about what is happening during drilling operations. Yet challenges persist. Each vendor might use a different tool to record drilling data, and that tool and its system are not always compatible with other equipment on the rig.
The result is a greater amount of more detailed data, but possibly scattered among several systems. This forces engineers to sift through even more data to find the critical information required to understand what is truly happening during the drilling operation. To address these inconsistencies, standards such as Wellsite Information Transfer Standard (WITS), Wellsite Information Transfer Standard Markup Language (WITSML), Modbus, Open Platform Communications United Architecture (OPC-UA), and more have emerged allowing data to flow more seamlessly between vendors, rig contractors, and operators.
When the data are collected and shared, independent tools may be used to visualize the data, conduct performance analytics, perform real-time drilling engineering calculations or compare real-time data to pre-job models. All of this is necessary to optimize the drilling process, improve ROP, reduce NPT, and identify or reduce ILT.
Operators desire a solution that seamlessly combines all of the above functions into the one easy-to-use, lightweight platform that functions not only for drilling, but spans across other operations including formation evaluation, mud logging, and well completions.
Integrating data into one digital environment. To address the industry demands and operational challenges, Weatherford has developed the Centro well construction optimization platform, a digital solution that provides exceptional visualization and performance enhancements in any operation. The Centro platform goes beyond merely transferring information between the rig and users anywhere in the world. Instead, this integrated, data-driven solution aggregates data from different vendors, data sources, and domains into one integrated, collaborative solution. The system builds on more than a decade of experience in real-time drilling services with innovative capabilities. Open aggregation, real-time modeling, and performance analytics combine to give engineers instantaneous insights, enabling field personnel to stay ahead of issues, identify opportunities for cost reductions, and ultimately deliver the well on time and on budget.
Five key processes ground the system: aggregation, monitoring, engineering, benchmarking, and optimization. The Centro platform’s aggregation acknowledges that information is collected from multiple vendors, multiple data sources, sensors both on the surface and downhole, and different domains with different types of data including rig sensors, mudlogging, directional drilling and MWD/LWD information, casing, geosteering, wireline, cementing, and completions. The system is vendor agnostic since the platform uses industry standard data protocols including WITS, WITSML, Modbus, and OPC-UA. The system may handle a data frequency of less than one/sec. And, for data security, the system features cybersecurity controls for comprehensive security measures, such as user and role-based access to specific data sets, single sign-on (SSO), multi-factor authentication (MFA), authentication using LDAP, Azure Active Directory (AAD), and application and data permissions (ACLs).
Visualization and real-time monitoring transform the data into digestible, fit-for-purpose usage. This is achieved by exploiting the diverse variety of visualizations such as standard time/depth log plots, 2D/3D displays, cross plots, histograms, dials and gauges, and digits. The configuration options for display are customizable and endless, but once users have the data the way they need to see it, dashboards can easily be saved and recalled for future use with the same well or any well, past or future. There is no limit to the flexibility or number of dashboards users can display to visualize, analyze, and interpret their data. The web-based platform is HTML5 compatible and supports multiple form factors such as desktop, tablet, or mobile. The multi-domain data sources that can be visualized include images, seismic data, drilling, mud, and log data, and 3D subsurface well construction data, Fig. 1.
Fig. 1. Integration and visualization of multidomain data.
This information can be presented using advanced visualization tools such as cross plots, statistical analysis, depth-gate time plots, and more. Further analytical capability extends to multi-well correlation including historical or offset wells plotted against current well data. Smart alarms are available in the platform but can also be user-defined and configured by the user to trigger visual or audible alerts on dashboards or alert users via email/SMS notifications. When immediate interactive discussions are required, a chat window can be used across the entire engineering team. This chat is then a permanent auditable record attached to the well or project. The Centro platform features flexible deployment options, and both on-premises or cloud-based are available. The platform serves as a centralized and secured repository for all streaming and recorded data sources, but also has a project level document storage and management feature.
The Centro platform also includes a full range of drilling engineering capabilities, available both for pre-job and real-time modeling. Developing pre-job models from historical and offset well data enables drilling engineers to efficiently plan each hole section, and respective BHA runs. Real-time data can be used to compare against historical data, as well as update, in real time, the same models that provide instant feedback to make immediate decisions. Available engineering models include hydraulics, torque and drag, swab and surge, hole cleaning and customizable user-defined calculations such as a stuck pipe prevention risk algorithm.
While it is possible to use the system to monitor the condition and activities of a well (or multiple wells), and perform real-time drilling engineering calculations, users have the ability to leverage the performance management dashboards and the automated summary reports to further engineer the processes and identify opportunities for cost reduction and savings. With single- and multi-well analysis, and extensive key performance metrics, an operator can determine how a well is being drilled with respect to overall corporate, drilling program, and individual well KPIs and make real-time adjustments.
Both high frequency data from rig sensors/downhole tools and low frequency data from historical or offset wells are combined to provide as much input and context into the performance models as possible. Statistical technical limits are calculated based on combining the best sections from available historical wells, producing an ideal well. This is then compared against the current well in real time. A host of KPIs are automatically calculated and displayed in easy-to-read dashboards that can be tailored to user roles such as drilling engineer, company man, geoscience, and more. Operators can also examine NPT, ILT, rig performance, crew performance, and other data points.
Finally, traditional physics-based drilling engineering models are being enhanced by new data-driven machine learning (ML) algorithms for predictive capabilities. Many companies are applying new ML models to optimize drilling but constraining these new algorithms with traditional physics-based models adds a level of accuracy, safety, and security to these newer algorithms. A combination of new and old provides the benefits of better computations with the security of known and trusted workflows and processes.
An operator of an onshore well in Mexico enjoyed the benefits and value of the Centro platform to improve operational performance. After repeated failures to achieve the planned total depth (TD) including three stuck-pipe events and eight days of NPT, the operator needed another option. Weatherford recommended the integrated solution approach provided by the Centro platform. The goal was not only to reach TD but to do so with two instead of three casing sizes.
Field personnel connected the Centro platform to rig data sent via WITSML to a secure, land-based data store. Technicians customized 15 real-time operational dashboards for different disciplines, ensured a robust data connection between Weatherford and third-party providers, and trained engineers involved in the project on functionality. A real-time operations center (RTOC) was built to support the maximum data load with 24x7 staffing.
During drilling operations, the Centro platform successfully acquired and aggregated all vendor-neutral data, securely stored it, and provided web-based, real-time visualization to a multidisciplinary team specializing in drilling, managed pressure drilling, and drilling fluids. More than 100 users from various asset teams, product lines, RTOC support personnel, the operator, and three external vendors all had access to the same real-time data.
Automated, condition-based alarms delivered early risk detection to the engineers, giving them ample time to respond to or avoid unplanned events. The continuous, real-time data was compared with simulation pre-drill models—including torque and drag, hydraulics, hole cleaning to possible hole problems, as well as pore pressure prediction to avoid differential sticking problems found in offset wells—all of which proactively helped field personnel avoid downhole issues (FIG. 2). Real-time data transmission during logging-while-drilling and pressure-while-drilling operations indicated formation changes while fully customizable multi-well, multi-domain operational dashboards helped the team to properly monitor key rig site operations. Monitoring of operations extended to the safe installation of all casings and real-time access for well testing operations.
Fig. 2. Real-time data is compared with models to avoid downhole issues.
The integration of services through the use of the Centro platform enabled the operator to drill the well to TD with less than 5% NPT and zero incidents. The well was completed 42 days faster when compared to the best offset well result, saving the operator 62% in rig time, with an approximate value of $1.8 million. After the well came online, its production rate was 32% higher than expected.
Reducing carbon footprint. Recently, performance metrics have extended into carbon reduction through evaluation of greenhouse gas (GHG) emissions from diesel generators supplying power to rigs. By combining rig activities with generator usage and load, GHG emissions and generator load were optimized to lower emissions, fuel consumption, and maintenance costs. By using both high and low frequency data based on historical and offset wells, KPIs can be calculated and compared to the current well being drilled, enabling drilling operations to be optimized in real time, delivering value to operators and rig contractors.
Increasingly, vast amounts of data are being generated during drilling operations. By using all of the available sources of data, both high and low frequency, the Centro platform can aggregate, monitor, engineer, benchmark, and optimize the drilling and well construction process. Engineers and managers across multiple domains and companies can collaborate on a single platform to increase drilling efficiency, reduce NPT and deliver wells faster and cheaper.
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