Singh, Ajay (Anadarko Petroleum Corporation) | Sankaran, Sathish (Anadarko Petroleum Corporation) | Ambre, Sachin (Anadarko Petroleum Corporation) | Srikonda, Rohit (Kongsberg Digital Inc.) | Houston, Zach (Kongsberg Digital Inc.)
Deepwater oil and gas facilities typically encounter on an average up to 5% annual production losses due to unplanned downtime, conservatively estimated at billions of dollars impact for the industry. The existing toolkit and systems in place are not always adequate to identify and predict abnormal events that could lead towards unplanned facility shutdown. The interaction amongst process sub-systems and disturbances that propagate across these sub-systems with changing operating conditions are hard to predict without a fit-for-purpose model (or a digital twin). The focus of current work is on deepwater facility having several oil export pipeline pumps in parallel and several gas compressors in series. The alarm database showed records of several unplanned shutdown events around these critical equipements that resulted in undesirable outcomes such as production deferment, complete facility shutdown, loss of sales volumes and increased operational costs. In this work, an intelligent prognostic solution is proposed using machine learning (ML) framework for automatic prediction of impending facility downtime, and identification of key causative process variables. A systematic workflow was developed to identify, cleanse and process real time data for both model training and prediction. Several ML methods were evaluated; anomaly detection based on Principal Component Analysis (PCA) and Autoencoder (AE) algorithms were found performing better for the type of data available for the deepwater facility. The ML framework also supported analysis of underlying downtime causes to propose suitable mitigation steps. Knowledge based on physical understanding of the process was used to select each sub-system boundary and sensor list on which ML model was trained. These models were then cross-validated to test the accuracy of trained models. Finally, the alarm database was used to confirm the accuracy of the machine leaning models and identify root-causes for unplanned shutdowns. If the operating condition changes over time, the anomaly detection based ML models were setup to adapt to changing conditions by automatic model updates, resulting in significant reduction in false alarms. The adaptive ML models, when applied to one of the sub-system (with 30 different sensor data), predicted 24 unplanned events in 6 months of period, while when applied to another sub-system (with 40 sensor data), predicted only 6 unplanned downtime events. Several predictions were found as early as 30 mins to 2 hours, providing adequate early warning to take proactive actions. Case studies shown in the paper present diagnostic charts and identified early indicators were found in agreement with pre-alarms generated by existing alarm system, thus validating the ML solution. Current toolkit available to identify anomalous process behavior is limited to exception based surveillance with fixed min-max limits on each sensor data. Therefore, proposed adaptive ML solution has shown potential to revolutionize the topside process surveillance. This paper also describes how the ML framework can be scaled for a sustainable solution that provides prediction every minute, keeps the model evergreen utilizing cloud-based model deployment platform to train, predict and trigger automatic model updates and also span multiple process systems and facilities. Finally, we present directions for future work, where the current model can keep predicting various events and over time when sufficient events are collected, more advanced machine learning methods based on supervised ML can be developed and deployed.
Se, Yegor (Chevron U.S.A. Inc) | Galimzhanov, Saken (Tengizchevroil) | Amangaliyev, Bolat (Tengizchevroil) | Aitzhanov, Abzal (Tengizchevroil) | Yechshanov, Ilyas (Tengizchevroil) | Iskakov, Elrad (Chevron U.S.A. Inc) | Ghomian, Yousef (Tengizchevroil) | Bopiyev, Chingiz (Tengizchevroil) | Wang, Haijing (Chevron U.S.A. Inc)
Sour gas injection (SGI) in the non-fracture platform area of the giant carbonate oil field, Tengiz, began in 2007. SGI project was proven to successfully maintain reservoir pressure in the platform area, add significant reserves, reduce sulfur production, and enable additional oil processing capacity at the crude processing facility. Despite the confirmed benefits, the gas breakthrough and increasing gas-oil ratio (GOR) trends in several SGI producers became a concern as the injection project matured. The preferential production from wells with lower GOR allowed higher total oil throughput, but also introduced production constrain on SGI wells with higher GOR. As the result, SGI producers were historically choked back or completely shut-in as soon as the gas breakthrough was confirmed and the producing GOR began to increase above 500m3/m3.
The reservoir heterogeneity with the sour gas injection overprint created complex dynamic environment at the subsurface. Special surveillance program was designed to improve understanding of gas front movement through the reservoir, assess vertical and areal sweep efficiency and remaining oil in place in various zones of interest. Surveillance program design had to overcome several operational constrains, such as wellbore accessibility issues from the scale build, gas handling limits of the surface facilities, and complex simultaneous operations near the active high-pressure sour gas compressor. Moreover, the log interpretation had to consider crossflow and stimulation chemicals impact on the logging measurements. Finally, the integration of logging interpretation results with reservoir model was required to improve the reservoir model forecast and boost the value of acquired information.
This paper describes the results of the conducted surveillance campaign, the novel calibration methodology of gas saturation profile from the time-lapse cased hole measurements with proxy from the multi-component simulation model output and the early results of the performed gas shut-off operations. The described methodology allowed direct calibration of the model outputs with the gas saturation results from pulse neutron logs and provided more accurate sweep efficiency and oil recovery forecast across the entire SGI area. Calibrated model revealed consistent gas breakthrough profile and significant volume of low GOR oil remaining in the wells with gas breakthrough.
The updated reservoir model was then used to evaluate various development scenarios of SGI area. Gas shut-off scenario showed particularly encouraging low GOR production trends and improved oil recovery especially from the lower intervals. After the economic analysis, several wells, including long-term shut-ins, were added to the workover queue to timely realize production benefits. Early production results after gas shut-off workover consistently met or exceeded model forecasts. Described methodology provided more accurate scope definition, value assessment and justification for the SGI optimization project and could be applicable to other improved oil recovery projects.
90% of Field T production relies on Gas lift as means of artificial lift. Typical surveillance strategy in assessing the health of the gas lifted wells is to deploy flowing gradient survey (FGS) in tandem with surface welltest. However, in the case of Field T, this technology meets its limitation in investigating prolific wells due to its current well mechanical condition and dual string completion environment. Welltracer technology application in the field has broken the barrier in evaluation of these wells in Field T.
The Welltracer application is a non-invasive data acquisition method which measures the travel time and concentration of the CO2 return which is introduced upstream of the gas lift header. The interpreted results allow for the identification of injection points and rate. This simple idea opens up opportunity for gas lift performance evaluation of wells in Field T that was not possible through the conventional approach of FGS. This breakthrough is vital for Field T as some of the wells are facing either one or more of the following problems i.e. dual string wells with gas robbing issues, tubing leak, restricted tubing due to pack-off and multi-point injection.
Twenty-three surveys and analysis were completed during the first application in Field T. The opportunity identified from the survey were categorized depending on the resources and timeframe required to execute the changes. Four enhancement opportunities were identified which only required surface valve manipulation were executed immediately and showed instant results. Other than additional barrels, the results of the campaign have a tremendous value of information that changed the earlier comprehension of the existing problems in some of the wells.
This paper discusses the results of the application of the technology in Field T. This paper will also elaborate on the lessons learned and improvement recommendations in terms of project identification, execution and planning. Another important highlight that will be discussed is the limitation and assumptions made to further enhance the understanding of the Welltracer technology.
Nguyen, Dzu (BP) | Macleod, Innis (BP) | Taylor, Donald (BP) | Murray, Laurence (BP) | Zavyalov, Denis (BP) | Booth, Dave (Fircroft Consultant, former BP) | Robertson, Neil (Halliburton) | Smith, Robert (Halliburton) | Joubran, Jonathon (Halliburton) | Allen, Clifford (Halliburton) | Shafei, Sharil Mohd (Halliburton)
The multiple zone water injection project (MZWIP) was initiated to deliver the following key objectives: deliver zonal injection with conformance control and reliable sand management across the major layered sands of the Balakhany unconsolidated reservoirs in the BP operated Azeri-Chirag-Gunashli (ACG) fields in Azerbaijan sector of the Caspian Sea.
Three years after MZWIP implementation, six wells with a total of 14 zones are injecting at required rates with zonal rate live-reporting. To achieve this multizone injection facility, the requirement for a standard ACG sand-control injector design was discounted and a non-standard sand management control technique developed using a cased & perforated (C&P) and downhole flow-control system (DHFC). During this program, BP ACG has successfully installed the world's first 10kpsi three-zone inline variable-choke DHFC wells with distributed temperature sensors (DTS) across all target injection zones.
The choking DHFC provides flexibility in operations and delivers the right rates to the right zones. The DTS provides conformance surveillance, fracture assessment, caprock integrity and sand ingress monitoring capability. A customized topside logic control system provides an automatic shutin of interval control valves (ICVs) during planned or unplanned shutins to stop crossflow and sand ingress and is the primary method of effectively managing sanded annuli.
The development of this MZWI solution has significantly changed the Balakhany development plan and has been quickly expanded across five ACG platforms. Accessing 2nd and 3rd zones in the same wellbore, this C&P DHFC well design is accelerating major oil volumes and will significantly reduce future development costs, maximizing wellbore utility in a slot-constrained platform.
Pavlov, Dmitry (Sakhalin Energy Investment Company Ltd.) | Fedorov, Nikolay (Sakhalin Energy Investment Company Ltd.) | Timofeeva, Olga (Sakhalin Energy Investment Company Ltd.) | Vasiliev, Anton (Sakhalin Energy Investment Company Ltd.)
This paper summarizes the results of 3 years collaborative efforts of the Geophysicist, Production Geologist and Reservoir Engineers from the Astokh Development Team and a Geochemist from the LNG plant laboratory on integration of reservoir surveillance and reservoir modelling.
In period 2015 – 2018 a large bulk of geological and field development data was collected in Astokh field, in particular: cased and open hole logs, core, open hole pressure measurements, flowing and closed-in bottom hole pressures, well test data, new 4D seismic surveys (2015, 2018), fluid samples. Since 2016, essential progress was made in oil fingerprinting for oil production allocation in Astokh field. Simultaneously, the need for update of static and dynamic models was matured upon gaining experience in dynamic model history matching to field operational data (rates, pressures, well intervention results). In other words, the need in update of geological architecture of the Astokh reservoir model was matured upon reaching critical mass of new data and experience. To revise well correlation, it was decided to combine different sorts of data, in particular seismic, well logs and core data and reservoir pressures. Different pressure regimes were identified for 3 layers within XXI reservoir. Pressure transient surveys were used for identification of geological boundaries where it's possible and this data was also incorporated into the model. Oil fingerprinting data was used for identification of different layers and compartments. Integration of pressure and oil geochemistry data allowed to identify inter-reservoir cross-flows caused by pressure differential. Based on all collected data, sedimentology model and reservoir correlation were updated based on sequential stratigraphy. As a result, a new static model of main Astokh reservoirs was built, incorporating clinoform architecture for layers XXI-1' and XXI-2. To check a new concept of geological architecture material balance model was used and matched to field data
Integration of geological and field operational data provided a key to more advanced reservoir management and development strategy optimization. Based on updated reservoir model, new potential drilling targets were identified. Also, with new well correlation, water flood optimization via management of voidage replacement ratio was proposed. The completed work suggests essential improvement in reservoir modelling process by inclusion of various well and reservoir surveillance data.
The paper consists of the following sections: Introduction Field geology Field development history Scope of work complete and main results Proposed well correlation update for XXI-1' and XXI-2 layers Integration of well logs, pressure and fluid analysis data Connectivity between layers XXI-S, XXI-1' and XXI-2 Integration of pressure and oil fingerprinting data Connectivity within layers XXI-S, XXI-1' and XXI-2 Results of pressure interference tests Testing of new well correlation concept in material balance model Proposed reservoir correlation updated based on seismic data New geological concept New depositional model Integration of core data Changes in reservoir architecture Conclusion Main results and impact on field development
Field development history
Scope of work complete and main results
Proposed well correlation update for XXI-1' and XXI-2 layers
Integration of well logs, pressure and fluid analysis data
Connectivity between layers XXI-S, XXI-1' and XXI-2
Integration of pressure and oil fingerprinting data
Connectivity within layers XXI-S, XXI-1' and XXI-2
Results of pressure interference tests
Testing of new well correlation concept in material balance model
Proposed reservoir correlation updated based on seismic data
New geological concept
New depositional model
Integration of core data
Changes in reservoir architecture
Main results and impact on field development
Integrated surveillance is critical for understanding reservoir dynamics and improving field management. A key component of the surveillance is areal monitoring of subsurface changes by use of time-lapse geophysical surveys such as 4D seismic. The purpose of the complete paper is to create a performance-based reservoir characterization by use of production data (measured rates and pressures) from a selected gas-condensate region within the Eagle Ford Shale.
This paper outlines the value of 4D for reducing uncertainty in the range of history-matched models and improving the production forecast. This paper describes interpretation results of a 4D seismic-monitoring program in a challenging Middle East carbonate reservoir. Integrated surveillance is critical for understanding reservoir dynamics and improving field management. A key component of the surveillance is areal monitoring of subsurface changes by use of time-lapse geophysical surveys such as 4D seismic. In this paper, the authors propose a new method for time-lapse-seismic surveys focused on water-injector wells.
The complete paper highlights elements of the technical development and an overview of the primary building blocks of the system, and presents in detail some of the challenges in developing, designing, and testing the control system. As the hunger for data grows, long stepouts become more common, and fiber communication becomes standard, the use of fiber in subsea oil and gas fields is set to increase. The paper provides a fast-track approach to perform screening assessment of multiple subsea concepts. Technologies are being developed that have the potential to support marine mining in all stages from prospection to decommissioning. These developments will likely have substantial influence in the oil and gas industry, itself searching for ways to maximize exploitation of assets.
Researchers from the Federal Reserve Bank of Dallas quantified the economic impact of the US shale revolution for the first half of this decade. Production from the Hibernia platform was shut down again on 17 August after its second oil spill in a month, while Husky Energy began to ramp up output from the White Rose field following the largest-ever spill off Canada’s easternmost province. Anchored by the Khaleesi-Mormont and Samurai fields, the King’s Quay FPS will receive and process up to 80,000 B/D of crude oil. Despite reports to the contrary, Permian well productivity remains healthy, with average new production per well in the basin matching all-time highs, Rystad says. Researchers mapped 251 faults in the North Texas home of the Barnett Shale, the birthplace of the shale revolution, finding that wastewater injection there “significantly increases the likelihood for faults to slip.”
This session focuses on the selection criteria for onshore and offshore waterflood, which had evolved with the availability of newer and cheaper water treatment systems and technologies. At the same time, practitioners will also need to look at parameters to ensure waterflood can be executed in a low oil price environment while covering the gas cap field reservoir quality. Other area which will be covered include local policies and requirements (how operators are involved), applications of industry standards, implementations of waterflood best practices and hydrocarbon recovery technologies.