Inserting a positive isolation spade on live pipe flanges is a game changer. The purpose of the tool is to enable safe isolations and to reduce extent and duration of production shutdowns, adding value of 2-20 MUSD per application. The principle design was developed within the Company addressing shortcomings of traditional isolation methods. The tool is field proven on a platform on the NCS.
Plants have large volumes which require substantial preparation and start up activities in relation to performing maintenance operations. The isolation tool can shorten shut down periods significantly thereby reducing cost.
Typical applications may include replacement of valves and piping, isolate heat exchangers for chemical cleaning or replacing leaking flange gasket with new gaskets and bolts. The live isolation tool can turn the original spectacle blinds on live systems, replace elements connected to piping systems, floating hulls, connections to high volume tanks.
The tool can be installed on a pair of flanges at the maintenance location and significantly reduces the need for drainage, venting purging and flushing.
A field proven tool for live process isolation has been demonstrates as a safe and cost saving technology. The technology is patented and is significantly different from existing methods of line stopping. There is a wide range of application areas in Facilities and Production Operations and the new tool will increase plant uptime.
The case study is based on the first field application of the live isolation tool on a 24" flange without draining the inventory. No conventional isolation methods were feasible in this isolation case to facilitate chemical cleaning of a heat exchanger thereby sustaining uptime in a large process plant on major offshore platform NCS.
This paper documents an initiative to develop a surface-activated, casing-integrated, flow-restriction tool capable of arresting flow during an uncontrolled blowout. The tool is similar in function to a subsurface safety valve (SSSV) but is designed to fit directly into a 9-5/8-inch casing string. Unlike a SSSV, the well restriction tool (WRT) described here is intended for use during drilling operations and can be installed deep in the well near the end of the casing string. The WRT is intended to supplement the blowout preventer (BOP) by arresting the influx of hydrocarbons into the well thereby increasing the chances that the BOP can successfully close, and by serving as a backup in cases where BOP closure is unsuccessful. Actuation of the device is accomplished by remotely triggering the combustion of a propellant charge which drives a sleeve forward and releases six, spring-loaded, triangular fingers which come together to seal the wellbore. This work describes the conceptual operation of the WRT and the design basis for the tool; including, computational fluid dynamics (CFD) analysis and finite element analysis (FEA). Lastly, initial prototype testing will be presented culminating in a successful closure and leak proof hydrostatic test to 10,000 psi.
Operators are looking to drill and develop deep-water wells with pressures over 15,000 psi and temperatures exceeding 300°F. Designing for high pressure, high temperature (HPHT) conditions present a number of engineering challenges, which can push conventional subsea technology designs to their limits. Therefore, there is a need to understand the feasibility of riser systems in these conditions and consequently to close any potential gaps between the current qualified technology and the outlined project specifications for a number of key riser components.
For conventional reservoirs, the merits of using wet tree and dry tree systems are well understood after years of design, fabrication, installation and operating experience. For HPHT riser applications, various design challenges exist with respect to the technology readiness of various riser system components of a wet or dry tree system development.
Key riser design issues and technology challenges, applicable to wet and dry tree HPHT systems, are addressed in this paper.
For a wet tree development, HPHT conditions require the use of thick wall pipes driven by burst sizing requirements, which in turn will lead to challenges associated with fabrication of pipes, pipe welding and inspection as well as meeting applicable sour service requirements. Furthermore, design of riser hang-off systems of wet tree applications is a critical area that requires consideration. The use of High-Integrity Pressure Protection Systems (HIPPS) to overcome HPHT obstacles is also discussed in this paper.
The use of high strength steel pipe with threaded mechanical connections provides a weight benefit for a dry tree system. However, the qualification of connectors is required and is expected to be a critical activity. In addition, the dry tree system has many other sealing surfaces and connections subject to HPHT loads at the surface and subsea wellhead locations, each of which presents their own design and qualification challenges.
Automated Safety Instrumented Systems (SIS) have evolved dramatically over the last 20 years becoming critical for mitigating risk and ensuring plant safety in the offshore and process industries. Data from HSE studies (see Figure 1) reveal that 44 percent of failures in safety shutdown control systems are due to insufficient specification. Studies such as this resulted in the development of new safety instrumented system standards ISA84.01/IEC61511 and IEC61508. However, these standards have left end users with little guidance on how to integrate and test these systems. Compliance has grown complex and costly for systems that are often the last line of defense in protecting personnel, the environment and nearby communities.
Predictive maintenance has become the paradigm of choice for the largest industrial companies because of the value it derives, including reduced downtime, improved efficiency, reduced maintenance costs, and others. Success of predictive maintenance programs is achieved when data, analytics, and subject matter expertise intersect. While data and subject matter expertise are always available, analytics talent is often lacking or facing numerous challenges which hinders the success of predictive maintenance programs.
Automated model building (AMB) aims at delivering artificial intelligence to the fingertips of industrial companies and hence ensuring the success of predictive maintenance programs without the need of large data science organizations.
The automated model building platform ingests the operational (sensor) and failure/fault data and automatically builds AI models to predict the remaining useful life for the asset. The patented technology behind the platform drives feature engineering and model selection which allows customers to automatically create numerous new variables from the sensor data and tests thousands of different models. The platform will then select the optimal set of variables and the model that will achieve the best performance.
The entire process can be performed in a matter of few minutes without the need to know the details of all AI models. The platform also gives details on the selected models, which aids with interpretability.
Modeling of long marine risers subjected to VIV is a challenging problem to solve using 3D Computational Fluid Dynamics (CFD) due to the high length-to-diameter ratio and usage of different VIV suppression devices. The scale of the problem can also get extremely large as the risers may have lengths up to thousands of meters, which makes it hard to use 3D CFD simulations. However, CFD is unique to capture complex flow around bluff structures and able to model risers with and without suppression devices and involve effects of nonlinear structural response inherently.
ExxonMobil's high quality data on the behavior of high length-to-diameter ratio (L/D) risers subjected to vortex induced vibrations (VIV) in uniform and sheared flow (
Pankaj, Piyush (Schlumberger) | Geetan, Steve (EP Energy Corporation) | MacDonald, Richard (EP Energy Corporation) | Shukla, Priyavrat (Schlumberger) | Sharma, Abhishek (Schlumberger) | Menasria, Samir (Schlumberger) | Xue, Han (Schlumberger) | Judd, Tobias (Schlumberger)
In today's data-driven economy, operators that integrate vast stores of fundamental reservoir and production data with the highperformance predictive analytics solutions can emerge as winners in the contest of maximizing estimated ultimate recovery (EUR). The scope of this study is to demonstrate a new workflow coupling earth sciences with data analytics to operationalize well completion optimization. The workflow aims to build a robust predictive model that allows users to perform sensitivity analysis on completion designs within a few hours.
Current workflows for well completion and production optimization in unconventional reservoirs require extensive earth modeling, fracture simulation, and production simulations. With considerable effort and wide scale of sensitivity, studies could enable optimized well completion design parameters such as optimal cluster spacing, optimal proppant loading, optimal well spacing, etc. Yet, today, less than 5% of the wells fractured in North America are designed using advanced simulation due to the required level of data, skillset, and long computing times. Breaking these limitations through parallel fracture and reservoir simulations in the cloud and combining such simulation with data analytics and artificial intelligence algorithms helped in the development of a powerful solution that creates models for fast, yet effective, completion design.
The approach was executed on Eagle Ford wells as a case study in 2016. Over 2000 data points were collected with completion sensitivity performed on a multithreaded cluster environment on these wells. Advanced machine learning and data mining algorithms of data analytics such as random forest, gradient boost, linear regression, etc. were applied on the data points to create a proxy model for the fracturing and numerical production simulator. With the gradient boost technique, over 90% accuracy was achieved between the proxy model and the actual results. Hence, the proxy model could predict the wellbore productivity accurately for any given change in completion design. The operators now had a much simpler model, which served as a plug-and-play tool for the completion engineers to evaluate the impact of changes in completion parameters on the future well performance and making fast-tracked economic decisions almost in real time. The approach can be replicated for varying geological and geomechanical properties as operations move from pad to pad. Although the need for heavy computing resource, simulation skillset, and long run times was eliminated with this new approach, regular QA/QC of the model through manual simulations makes the process more robust and reliable.
The methodology provides an integrated approach to bridge the traditional reservoir understanding and simulation approach to the new big data approach to create proxies, which allows operators to make quicker decisions for completion optimization. The technique presented in this paper can be extended for other domains of wellsite operations such as well drilling, artificial lift, etc. and help operators evaluate the most economical scenario in close to real time.
Garan, Ron (Clariant Oil Services) | Esley, John (Clariant Oil Services) | Arciero, Bryan (Murphy Exploration & Production Company) | Mazzeo, Claudia (Clariant Oil Services) | Alapati, Rama (Clariant Oil Services) | Yousef, Ali (Clariant Oil Services)
Prior to a planned transition in producing zones, an 18,000′ single well subsea tieback flowline to a deepwater Gulf of Mexico production facility experienced a restricted flowline ID and partial blockages due to paraffin deposition. Efforts were coordinated to provide support in the design, product selection, and determination of success for the flowline remediation. Transient multiphase flow simulations were created and tuned/validated with historical slugging data to estimate initial effective ID of the subsea flowline. The models were then applied to the planned clean-out procedure to develop performance indicators during and after flushing operations. A two-step remediation consisting of a 24 hour hydrocarbon solvent/dispersant mixture soak, followed by a 4,000 bbl seawater and waterbased paraffin dispersant flush at increasing rates utilizing solvency, dispersancy, and shear was used to remove deposition and increase cross-sectional flow area of the pipeline by 85% (initial effective ID ~2.5 in., final effective ID ~3.4 in.). The procedures were created to minimize risk of packing solids following initial disaggregation, while maximizing effectiveness of the flowline clean-out within the economic constraints of a depressed oil market.
Cui, Yunjiang (Tianjin Branch of CNOOC Ltd) | Shi, Xinlei (Tianjin Branch of CNOOC Ltd) | Li, Ting (Schlumberger) | Wang, Ruihong (Tianjin Branch of CNOOC Ltd) | Lu, Yunlong (Tianjin Branch of CNOOC Ltd) | Meng, Li (COSL Ltd)
In this case study, we examine permeability estimation in a Middle East carbonate field where oil is mainly produced from the Cretaceous limestone reservoirs. Due to the complex depositional and diagenetic processes, the reservoir rocks exhibit significant heterogeneity in petrophysical properties. In the industry, it is a common practice to estimate permeability with porosity vs. permeability (poroperm) relationships derived from core data. However, in our study field, the semi-log crossplots of core porosity and permeability generally exhibit a wide spread. As a result, the poroperm models determined from these crossplots can make quite inaccurate predictions about permeability.
In sedimentary rocks, variations in pore geometrical attributes define distinct flow units. Within each flow unit, the rocks exhibit similar fluid-flow characteristics and consistent petrophysical properties. Therefore, core samples belonging to the same flow unit generally exhibit better porpoperm correlations than those from the entire well. Based on this principle, we first classify reservoir rocks into a number of facies and then define a poroperm relationship for each facies based on core measurements. The method requires a set of well logs sufficient to classify the reservoir rocks into the distinct facies. In some cases basic logs such as GR, density and neutron porosity will be sufficient, but in other cases additional logs will be required to correctly differentiate the facies. Core measurements are only needed in a key well penetrating the reservoirs under study. The following is the detailed workflow:
Apply a clustering algorithm to well log curves to assign facies to cored intervals.
For core samples in each facies, develop a poroperm relationship based on measured core porosity and permeability in this form: logK = A*phi+B.
Train a self-organizing map with well log patterns associated with each facies at the cored intervals and propagate the facies classification to un-cored intervals using select log curves.
Use the poroperm relationships defined for different facies to calculate a continuous permeability curve for the entire well.
In our study field, wireline triple combo logs and core data were collected in 7 wells. The clustering algorithm identified 5 facies from cored intervals in one key well. The facies classification was then propagated to un-cored intervals in the 7 wells using well logs. Based on core data from the key well, 5 poroperm relationships were established for the 5 facies using regression and continuous permeability curves were calculated from these relationships for the 7 wells. There is an excellent match between predicted and core permeability in all 7 wells. In contrast, a single poroperm relationship that ignores rock facies produces permeability predictions that fail to reflect the full variation in the core measurements in each well. In this report, we show the interpretation results from two wells as validation of the proposed workflow.
Amongst all the several threats derived from corrosion in bolting in marine environments, hydrogen embrittlement is perhaps one of the most dreaded. Hydrogen embrittlement is a form of environmentally assisted cracking (EAC) where hydrogen generated from different sources penetrates inside the basematerial and makes it more fragile. This paper addresses the severity of the environment and the influence of different metallic coatings on the amount of hydrogen present in the base substrate steel bolting. From laboratory generated data, environmental severity and risk of hydrogen embrittlement are estimated and correlated to actual field performance from the literature. This investigation relates the interplay of environment, stress, and materials.
The metallic coatings evaluated in this investigation are: Zinc, Zinc-Nickel, and Nickel-Cobalt ASTM B994, the two formers are typical coatings currently used in bolting in Oil and Gas, the latter is a novel material with offshore applications including subsea environments. Cracking resistance of the AISI 4130/4140 and 4340 also specified as ASTM A193 B7/B7M, L7/L7M and L43 studs or bolts and ASTM A194 nuts, all referred to as bolting, is characterized in terms of the variation in environmental severity. The environmental severity is measured by both, Devanathan–Stachurski cell technique to measure the amount of hydrogen absorbed into the steels substrate across the coatings, and the use of Tafel scans of the coatings and a Pourbaix diagram to measure Ecorr and amount of hydrogen generated. From these results, the metallic plated coatings are ranked as to environmental severity relative to each other.
The results showed an outstanding performance of the Nickel-Cobalt coating compared to the sacrificial coatings. Sacrificial coatings produced large amounts of hydrogen in the cathodic reaction and allowed its penetration to the base-material; Nickel-Cobalt did not produce hydrogen at OCP and the permeation was much lower than in the other materials under cathodic charging conditions. The results of mechanical testing showed that Nickel-Cobalt is not affected by the cathodic charging whilst the tested sacrificial coatings reduce their mechanical resistance in a 50%; these results mean that hydrogen permeation into Nickel-Cobalt is negligible, even after being subject to high cathodic charging. Nickel-Cobalt alloy ASTM B994 is proposed as the emerging technology for carbon and high strength steel bolts to be used in marine environment and subsea where failure is not an option.
The results from this effort have an outstanding relevance in offshore and subsea deep-water drilling and production equipment that depends on high strength carbon and low allow steels. This work addresses failures caused by hydrogen embrittlement that have been documented by the American Petroleum Institute (API) and the Bureau of Safety and Environmental Enforcement (BSEE).