Africa (Sub-Sahara) Oil was discovered at the Ekales-1 wildcat well located in Block 13T in northern Kenya. The well has a potential net pay of between 197 and 322 ft in the Auwerwer and Upper Lokone sandstone formations. Tullow (50%) operates 13T with partner Africa Oil (50%). The Mzia-3 appraisal well in Block 1 off Tanzania encountered a combined total of 183 ft of net pay in the Lower and Middle sands and confirmed reservoir quality in line with that seen in the Mzia-1 and Mzia-2 wells. Asia Pacific The Luba-1 offshore well on Brunei Block L was spudded. The well will evaluate the hydrocarbon potential of the Triple Junction structure. Serinus has a 90% interest in Block L, through indirect wholly owned subsidiaries Kulczyk Oil Brunei (40%) and AED SEA (operator, 50%).
Africa (Sub-Sahara) Eni finished a production test on its Minsala Marine 1 NFW well, located in Marine XII block, 35 km offshore The Republic of the Congo. During the test, the well delivered natural flow in excess of 5,000 B/D of 41 API crude and 14 MMcf/D of natural gas from a 37-m opened section of the discovery's 420-m column. Eni (65%) is operator, with state-owned partner SNPC (25%), and New Age (African Global Energy) Limited (10%). Asia Pacific CNOOC started natural gas production from the Panyu 34-1/35-1/35-2 project at the Pearl River Mouth basin in the South China Sea. Main production facilities for the three gas fields include one comprehensive platform, two sets of underwater production systems, and 13 producing wells. Two wells are producing a total of 21 MMcf/D of gas. The project is expected to reach peak production of 150 MMcf/D.
Digital oil fields implementation is ongoing in various oil fields around the world since the last few years. There are many research initiatives focusing on performance improvements trying to eliminate Non-productive time (NPT) caused by equipment failures or drilling conditions but the Invisible Lost Time (ILT), which accumulates when common drilling operations such as drill pipe connections are not carried out efficiently, is neglected. This makes it difficult to compare well delivery time and performance discrepancies for each activity across a field. The main challenge in optimizing drilling performance is deciphering the rich data streams in real time to make informed business decisions. This study focuses on the integration and analysis of real-time drilling data in order to evaluate the drilling performance via Invisible Lost time.
The methodology starts with analysing the effectiveness of the Remote Monitoring (the backbone of Digital Oil Field) of critical drilling operations as the actual performance is compared with predefined operation practices in terms of Rig Performance, Individual Crew Performance and Section Performance over four unknown drilling wells located within Field-X in the North Sea. The Invisible Lost Time is quantified from selected drilling activities such as tripping, drilling, running casing and flat time operations that can result in significant potential savings other than the main drilling operations.
Histograms were utilized to improve rig performance which indicated that the Connection time can lead to significant days’ savings as Tripping time contributes to approximately 60% of the Invisible Lost Time (ILT). Additionally, the effect of various factors such as hole sections and well depth on potential savings was also studied. This strategy may be developed as a cost-effective technology for any drilling or workover wells, as it results in improving drilling key performance indicators (KPI's) leading to performance improvement, risk mitigation and cost efficiency in real-time drilling activities.
Fomin, Vitaliy (Halliburton) | Kushmanov, Pavel (Halliburton) | Purwar, Suryansh (Halliburton) | Aksenov, Mikhail (Halliburton) | Durygin, Nikolay (Halliburton) | Golovin, Oleg (Halliburton) | Solovyev, Iliya (IPOS) | Govorkov, Denis (TSOGU) | Vedernikova, Yuliya (TSOGU) | Iskakov, Daulet (TSOGU)
Gas condensate fields present unique challenges regarding data acquisition, data quality, exception-based surveillance, flow modeling, nodal analysis, well testing, allocation, and visualization. Although existing tools and methods address many of these aspects, it is possible to streamline processes and explore increased production efficiency methods. This paper addresses these challenges; it presents a case study of an intelligent control system implementation for a gas-condensate field based on a unified data model, integrated modeling, and cross-domain workflows.
This paper presents a transformative, intelligent, and automated work process, referred to here as "smart workflows." As part of these workflows, virtual gauges are used that are based on inflow models and lifts, adjustable valves, and modular networks. The workflows are implemented on a truly open end-to-end platform that enables the coupling of multiple databases, streamlining of data for an integrated analysis of the measurements and model calculations, and ascertaining the mismatch between the two. The workflows also initialize adaptive self-tuning procedures.
The smart workflows enable engineers to achieve various improvements, including an integrated structure of process data model to enable quick access to validated data, monitoring and control functions to a gas-condensate field in real time, and reduced downtime and operational costs. The smart workflow also supports functions that include collection and verification of measurement data, configuration of the integrated solution component models, evaluation of the action of root causes, and planning of operation scenarios.
As part of the implemented system, an integrated information system data structure sets the degree of relatedness of tasks, each of which can be initialized depending on work situations and/or operator commands.
Such comprehensive analysis of the data provides reliable integrated system configuration parameters of the model, which increases the accuracy of the calculations used in the optimal planning of the operational scenarios.
Singh, Deepak (CSIR-National Geophysical Research Institute, Hyderabad, India) | Kumar, Priyadarshi Chinmoy (CSIR-National Geophysical Research Institute, Hyderabad, India) | Sain, Kalachand (CSIR-National Geophysical Research Institute, Hyderabad, India)
The chimney effects also exhibit good correlations with seismic attributes when displayed over the horizon slices mapped over the formation tops. This study provides important inputs in understanding the petroleum system of the study region and acts as a preventive measure for mitigating geo-hazards in future drilling. Introduction The state-of-the-art image processing and visualization techniques have modernized the art of seismic interpretation. This has allowed interpreters to analyze more data with a greater accuracy in less time. Seismic attributes have played a pivotal role in interpreting seismic data.
Time-lapse, cased hole torque and drag (T&D) measurements and soft string T&D modeling were undertaken in two experimental horizontal steam injection wells for the purpose of assessing the integrity of the slotted liner completions over a 20 month period. A series of progressively complex completions were installed in the wells to manage steam conformance and measure steam injection flow profiles in this mobile, heavy oil application. This T&D work was done to understand if sand influx, scale and asphaltene deposition, or thermal strain damage was occurring within the slotted liner thus increasing the deployment and recovery risk of the tubing-deployed completions. For each injector, T&D measurements were repeatedly obtained at the same depths during each workover with the same 3-1/2 inch (89 mm) tubing string.
T&D data is inexpensive and easy to acquire during rig operations. Commercial software is readily available to model T&D and estimate cased hole friction factors (CHFF). Analysis of T&D in these wells did provide insights for sand influx and scale deposition. However, T&D analysis did not provide insights into all integrity problems encountered which included metal clamp debris that would not allow packers to be landed at the target depth and corrosion failures resulting in parted tubing. T&D measurement analysis is a useful integrity diagnostic in horizontal injectors, but needs to be supplemented with other information to get a complete picture of wellbore conditions. Considering the general lack of information that heavy oil operators get from the horizontal section of their wells, it is recommended that baseline cased hole T&D measurements be acquired on horizontal wells during initial completion with 0.1 Kip precision. Comparing both T&D measurements and CHFF's on subsequent workovers did provide insights on the stability of horizontal wellbore conditions.
The world's first deployment of an automated drilling control system on a Statoil rig in the North Sea helped the rig in saving up to 10% rig time per well through safeguarding and optimizing manual operations and through automating repetitive drilling activities such as tripping, pipe filling, connections and pump start up. Advanced modelling of well conditions, combined with closed loop control of the drilling control system provided safeguards for pressure, rotary and hoisting velocity.
The drilling instrumentation, surface- and downhole sensors are coupled with robust real-time and fully transient hydraulic, mechanical and thermodynamic models that continuously evaluate the current downhole conditions. These models determine all possible combinations of drillers' actions (string accelerations, velocities, rotation, pump start-ups and flow rates) that will cause the dynamic downhole pressure to reach or exceed upper and lower well stability- and geo-pressure prognosis. These results are actively used to safeguard both manual and automated sequences. For example should the driller attempt to pull the drill string at a velocity that would cause the downhole pressure to fall below the Pore Pressure or Collapse Pressure at any depth in the open hole section, the drilling control system will intervene and limit the upward velocity to a safe value based on the dynamic model.
The models effectively calculated and communicated current limits to the drilling control system, allowing the control system to safeguard the well against human error during manual operations and to automate various repetitive operations. Statistics after 3 wells proved an overall time saving of 4% per well through automated repetitive sequences (such as pump start-ups and friction tests) while another 2–8% time savings per well were realized through optimized manual operations (active safeguards and safety triggers) and other improvement initiatives by the rig. Although the system was originally developed to eliminate human errors and avoid major incidents (including technical side-tracks), the daily efficiency gains indicate that the system also avoids minor issues that otherwise would have slowed down the operation without being seen as downtime or Invisible Lost Time. This indicates that the system works as intended and that the system should be able to avoid major incidents when the relevant conditions arise.
This paper demonstrates how automation reduces invisible lost time and allows drillers to focus on other activities while repetitive tasks are controlled by software. Furthermore, rig safety is significantly enhanced since the closed loop drilling control system prevents users from exceeding the dynamic limits calculated by the drilling control system.
Marron, A. J. (OMV E&P GmbH) | Milner, M. (OMV E&P GmbH) | O'Hagan, A. (OMV New Zealand Ltd) | Biniwale, S. S. (Schlumberger) | Trivedi, R. (Schlumberger) | Simpson, T. (Schlumberger) | Tran, A. C. (Schlumberger)
The Maari oil field, the first OMV operated offshore oil field development, has showcased OMV's impressive technical skills. Following the completion of a field re-development drilling campaign in August 2015, the well configuration currently consists of 10 producers and 1 water injector (with the option to convert a producer into a water injector in the future). Electric Submersible Pumps (ESPs) are installed on all 10 producing wells to provide lift of reservoir fluids to surface. A SCADA system and associated Production Historian Database (PHD) was included in order to capture the high frequency data for well & reservoir surveillance and daily production optimisation of the field. However, there were many challenges in utilising this live data stream from the offshore facility. In particular, it was vital to continuously and effectively monitor and optimise ESP performance in order to improve run life, reduce downtime and ultimately increase production. An integrated decision support system was therefore required for real-time data collection, production monitoring, ESP health check and KPI analysis for proactive decision making and limiting the number of manual processes involved.
This paper describes how these challenges were overcome by creating an integrated workflow and aligning the existing system architecture in order to meet the business needs. The system is based on full workflow automation, and has been deployed for data acquisition, validation and analysis by optimising the components of integrated asset management. The system includes an integrated framework connected to various live data sources with different time increments, allowing data aggregation to a reliable intra-day hub. Automated job scheduling has also been built in with a decision support dashboard setup for production analysis and ESP performance monitoring. Based on historical trends, an optimum operating envelope was defined and automatic rules were configured for anomaly detection.
The system has provided standardized data access throughout the asset team, streamlining their entire process and resulting in improved efficiency, which has optimised the engineers time for core operational activities. With a secure and automated workflow, and the ability for multiple users to work simultaneously, the system has minimised their downtime, thus improving overall productivity. Utilizing the live data feed for updating of simulation models has allowed quicker comparisons of numerical predictions with analytical forecasts, hence helping to streamline the overall reservoir management of the field. The system has not only assisted the team in meeting their production reporting deadlines, but has also alleviated bottlenecks in their decision-making processes helping to boost overall asset productivity.
An analysis was carried out to determine if 3D seismic could be used to build a subsurface model, revealing in detail where gas escape chimneys feed shallow gas accumulations, allowing the shallow hazards to not only be mapped accurately and risk reduced, but also indicate the relationship to the target reservoir itself. The method used techniques that exploited the potential
Shallow hazards in offshore oilfield developments often come in the form of gas chimneys and shallow gas emplacements, and can endanger the integrity of rig or platform foundations as well as ongoing drilling operations. Therefore mapping them accurately prior to any drilling or development operations can be critical for safety, and reducing costs due to interruptions.
An analysis was carried out to determine if 3D seismic, interrogated in a data driven but interpreter guided fashion, could be used to build a subsurface model revealing in detail where gas escape chimneys feed shallow gas accumulations, allowing the shallow hazards to not only be mapped accurately and risk reduced, but also inform the risk of trap leakage. Modern high-resolution 3D seismic is often more than adequate to locate such features and capture their extents, is available from the main reservoir interpretation at no extra cost, and with its large areal coverage can locate and prioritize targets for ultra-high resolution shallow hazard surveys. Additionally, complex feature morphologies can be captured using semi-automated techniques that are impossible to define using manual interpretation on a vertical slice-based approach.
A dataset over the Maari field, Taranaki basin, offshore New Zealand was used for the analysis. The survey has a lateral resolution of 25m by 12.5m and a vertical sample rate of 4ms. The reservoir is composed of several Miocene and Eocene pay sands layered in a four-way closure, and although the field was discovered in 1983, it was not produced from until 2009, due to complexities of commercialization requiring many injection and production wells. Issues included the relatively shallow depth of the reservoir (1300m TVD), cold temperatures and waxy oil. In the Moki sandstone alone six horizontal production wells with ~11,000m of section have been drilled, accompanied by three deviated water injectors. This complexity increases the importance of a thorough subsurface understanding of hazards and their geometries, and the significance of shallow hazards has been identified throughout.
Integrity management of mooring systems on floating structures has been gaining interest over the last few years, as a result of increasing interest in life extension of existing assets and the reported increase in the number of mooring system failures. During the second half of 2012, OMV New Zealand Ltd commenced planning for a detailed inspection program of all underwater assets in the Maari Field, including the mooring system for the FPSO Raroa. When conducting the campaign in early 2013, a series of anomalies were found, including birdcages in wire sections of adjacent mooring legs. Through a regime of coordinated metocean forecasting, metocean monitoring, FPSO position monitoring, numerical modelling and ongoing inspection, OMV New Zealand was able to effectively manage an FPSO found to have multiple adjacent degraded mooring lines through a winter season until repairs could be completed. The development of a concurrent numerical model of the actual mooring system proved to be indispensable in achieving this objective and in facilitating the day-to-day operation of the facility over this period. Being able to verify numerical predictions against actual vessel motion response data in combination with detailed site metocean data significantly enhanced the value of the numerical model. The numerical model was employed across a wide range of activities from forecasting performance, evaluation of hypothetical multi line failure scenarios, interpretation of measured performance, determination of sea state limits and inspection triggers, through to the remediation engineering of the system. Of particular importance for the Maari situation was the early detection of potential line failure on the degraded leeward mooring legs, which was heavily reliant on comparisons of numerical predictions against observed system behavior.