Subsea Blowout Preventer Research Articles

Technology Focus: High Pressure/High Temperature (March 2020)

Technology Focus One would think that, in these challenging times, high-pressure/high-temperature (HP/HT) technology and projects would be put on the back burner, with everybody chasing zipper-fractured barrels from shale. Well, it is not so. The rewards in new reserves and profits of being able to develop HP/HT resources efficiently are just too attractive to ignore. So, we can enjoy some major developments on the project and technical side in the past year, and the highlights are offshore. Let us look at the Gulf of Mexico, which has moved from being just a pioneering area for deepwater developments to an area where deep water and HP/HT combine to provide the ultimate challenge for the best engineers. In 2019, we saw first oil from Appomattox, the first producing high-temperature development in the deepwater Gulf of Mexico; and we can congratulate Shell (operator), Nexen, and the China National Offshore Oil Corporation for a job well done. This project also served as the developing ground for the recently issued Bureau of Safety and Environmental Enforcement HP/HT guidance documents, which certainly will make the next projects more streamlined. And lest we forget, it is also a “green” project, with the first combined-cycle power generation facility deployed offshore in the Gulf of Mexico. The next challenge is now the “HP” part of HP/HT, and Chevron took up the gauntlet and is putting the final touches on a new generation of drillship together with Transocean as the drilling contractor, with NOV providing dual 20,000-psi subsea blowout preventers. And, with the sanctioning of the Chevron-operated Anchor 20,000-psi development in the Green Canyon area at the end of 2019, it is anybody’s guess where this drillship will be deployed first. Total is the partner on this development. These two major HP/HT breakthroughs have been made in deep water, in the toughest industry environment seen at least in my lifetime. Who says our industry is not resilient and innovative? In this year’s paper selection, we are focusing on three technical areas where HP/HT and deep water come together: very-high-pressure and -temperature (supercritical) fluid properties, the latest expandable technology used for liner hangers, and the effect of ambient pressure on the pressure rating of well-construction equipment. Who would have thought that, in these challenging days, we would be able to celebrate the marriage of deep water and HP/HT? And this is happening not just in the Gulf of Mexico; we also hear some very interesting developments in Asia/Pacific (the South China Sea) and in the eastern Mediterranean. It is not aerospace or Silicon Valley, but our industry that is still the most innovative and pioneering in the word. We can only hope that the many highly qualified graduates, and especially post-graduates, in petroleum engineering looking for their first jobs are invited on this journey and don’t wander into other industries where their skills would be quickly appreciated. They are the ones we need to use all the new digital tools, such as simulator-based predrilling exercises. From the days of Shearwater to Appomattox and Anchor, we have almost no time left to tap the experience of the deepwater and HP/HT pioneers who are at the tail end of their careers and have so much knowledge to transfer. Recommended additional reading at OnePetro: www.onepetro.org. SPE 195353 Active Cooling Method for Downhole Systems in High-Temperature Environments by Wenkai Gao, China National Petroleum Corporation, et al. SPE 195725 Improving Performance in Elgin HP/HT Infill Drilling Despite Increasing Challenges by Mohammad Alahmad, Total, et al. SPE 197207 Improved Well Design 15,000-psi Cemented Completion To Deliver Faster and Cheaper Complex Deep Gas HP/HT Wells by Hashil Nasser Said Al Naabi, Petroleum Development Oman, et al.

A Switching MPD Controller for Mitigating Riser Gas Unloading Events in Offshore Drilling

Summary Riser gas unloading events in subsea well construction are hazardous and difficult to control. When a gas influx enters the wellbore and dissolves in nonaqueous fluids (NAFs), it may go unnoticed because the pit gain on the surface may be minimal and remain below the detection threshold when using conventional well control indicators. Once the dissolved gas is circulated up and comes out of the solution at pressure and temperature conditions below the bubblepoint, it can quickly displace a large volume of mud in the riser or the chokeline. When this breaking out of gas occurs at a shallow depth, it leaves little time for the rig crew to react. In this paper, we present a novel managed pressure drilling (MPD) approach for riser gas unloading control that makes use of a pressurized riser drilling (PRD) controller. The PRD method employs the constant bottomhole pressure (CBHP) controller for normal operations (e.g., drilling and circulation of kick), whereas it offers a more comprehensive way to manage and control a riser gas unloading behavior. The PRD choke controller dynamically applies a backpressure on the dissolved gas–NAF mixture in the riser to delay, minimize, or even prevent the gas breaking out at locations closer to the surface. The control algorithm considers the pressure limits of the riser and of the openhole formations and can adjust for kick uncertainties (e.g., whether the kick is a gas, liquid, or both, its volume and distribution). The proposed PRD controller consists of three operation modes: pressure control mode, flow control mode, and solubility control mode, with each mode applicable to its corresponding operating condition. The controller can automatically switch among different modes on the basis of the observed kick behavior, thereby gaining the ability to compensate for the limitations of the individual control modes and, more importantly, to deal with kicks agnostically, i.e., independent of their nature. The proposed controller is evaluated by simulating different riser gas unloading scenarios. Here, two distinct cases are given special consideration: (1) the case in which the subsea blowout preventers (BOPs) remain open after the kick passes them and the controller regulates the pressure using the maximum allowable surface pressure (MASP) or downhole fracture gradient as an upper limit and (2) the case in which the subsea BOPs are closed after the kick passes them and the controller regulates the pressure within the riser pressure limits when the kick is circulated to the surface using the riser booster pump. Simulation results show that the proposed controller can quickly and robustly control the riser gas unloading situations with complicated transient conditions, without fracturing downhole formations or jeopardizing the pressure integrity of the riser. The developed PRD controller aims to help mitigate some of the concerns about riser gas unloading when the dissolved gas is allowed to pass the subsea BOPs and enter the riser and to facilitate the implementation of more automated subsea well control using MPD technology in the foreseeable future.

Reliability analysis of subsea blowout preventers with condition-based maintenance using stochastic Petri nets

Blowout Preventer (BOP) has maintained its function as a safety barrier and the last line of defence against oil and gas spills since its development in the early 1900s. However, as drilling and exploration activities move further offshore, challenges pertaining to reliable operation of the subsea BOP systems continue to be a source of concern for stakeholders in the industry. In spite of recent advancements in reliability analysis of safety instrumented systems (SISs), the research on reliability assessment of BOP is still lacking in some regards. There are gaps in the literature with respect to the incorporation of preventive maintenance (PM) strategies as well as dynamic operating conditions into BOP reliability analysis. To address these gaps, this paper develops an advanced analysis method using stochastic Petri nets (SPN) to estimate the reliability of subsea BOP systems subject to condition-based maintenance (CBM) with different failure modes. The BOP system is divided into five subsystems which are connected in series with each other and categorised into degrading and binary units. The performance of the BOP system in terms of availability, reliability and mean-time-between failures (MTBF) is obtained and analysed. A sensitivity analysis is also performed to evaluate the effect of fault coverage factor and redundancy design on system performance. The results show that both the fault coverage factor and redundancy have significant impact on the BOP's reliability, availability and MTBF.

Reliability analysis of dynamic reliability block diagram based on dynamic uncertain causality graph

A dynamic reliability block diagram (DRBD) is often used in various industrial fields because of its ability to represent the dynamic behaviours of systems, despite its difficulty dealing with common cause failures and its quantitative result being hard to obtain due to the lack of a simple and practical solution method. Although some techniques, such as Petri net, Markov chain, and dynamic Bayesian network (DBN), have been proposed for analysing DRBDs, they are usually complicated and impractical for various reasons, such as state explosion in a Markov chain and a DBN and a complicated conversion process for a Petri net. To alleviate these problems, a common cause failure block is added to the DRBD, and a new solution method based on a dynamic uncertain causality graph (DUCG) is presented in this paper. Based on the conversion rule, the DRBD is mapped into a DUCG that needs fewer parameters and can be easily analysed according to the DUCG's reasoning algorithm. Finally, considering a subsea blowout preventer (BOP) control system as an example, a more accurate and concise model of the BOP control system is built.

An Integrated FTA-FMEA Model for Risk Analysis of Engineering Systems: A Case Study of Subsea Blowout Preventers

Engineering systems such as energy production facilities, aviation systems, maritime vessels, etc. continue to grow in size and complexity. This growth has made the identification, quantification and mitigation of risks associated with the failure of such systems so complicated. To solve this problem, several advanced techniques such as Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), Reliability-Block Diagram (RBD), Reliability-Centered Maintenance (RCM), Monte-Carlo Simulation (MCS), Markov Analysis (MA) and Bayesian Networks (BN) have been developed in the literature. In order to improve the strengths and eliminate the drawbacks of classical techniques, some hybrid models have been recently developed. In this paper, an integrated FTA and FMEA model is proposed for risk analysis of safety-critical systems. Minimal cut sets derived from the fault trees are weighted based on Birnbaum’s measure of importance and then the weights are used to revise Risk Priority Numbers (RPNs) obtained from the use of traditional FMEA techniques. The proposed model is applied to a Blowout Preventer (BOP) system operating under erratic and extreme conditions in a subsea oil and gas field. Though those failures caused by kill valves and hydraulic lines remain among the top risks in the BOP system, significant differences are revealed in risk rankings when the results from the hybrid approach are compared with those obtained from the classical risk analysis methods.

A Bayesian network based method for reliability analysis of subsea blowout preventer control system

Subsea drilling needs extremely complex equipment, but engineering challenges are posed by harsh offshore environments. A subsea blowout preventer (BOP) is a critical device used to seal, control and monitor oil wells to ensure safety during the drilling process. In this paper, a novel approach to construct an equivalent Bayesian network (BN) from a GO model is proposed and it is used for assessing reliability of the subsea BOP control system. The proposed method relaxes some limitations of GO models and enriches the ways of developing BNs. Probability updating and adaption of the presented BN is demonstrated by case studies. A three-axiom-based validation method is used for partial validation of the BN. The proposed method can be applied to other existing GO models.

Managed-Pressure-Drilling Equipment Augments Deepwater Well Control

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 186331, “Augmenting Deepwater Well Control With Managed-Pressure-Drilling Equipment,” by Austin Johnson, SPE, Brian Piccolo, Henry Pinkstone, SPE, Bo Anderson, and Justin Fraczek, SPE, AFGlobal, prepared for the 2017 SPE/IATMI Asia Pacific Oil and Gas Conference and Exhibition, Bali, Indonesia, 17–19 October. The paper has not been peer reviewed. This paper describes how a technique known as applied-surface-backpressure managed-pressure drilling (ASBP-MPD) can alleviate the limitations of conventional deepwater well control. The paper discusses equipment design and operating philosophy, outlining actions that can be taken to respond to an influx while remaining within the primary well barrier. Conventional Well Control: Background and Limitations Industry personnel are trained to follow conventional well-control-response steps when securing a well and closing a subsea blowout preventer (SSBOP) once an influx is detected. The steps are logical from the perspective of adhering to the operating requirements of existing well-control equipment. While variations in procedures exist between companies, the logic behind these steps remains consistent across the industry. The conventional steps are as follows: Stop rotating; pick up off bottom and space out Stop the mud pumps Conduct a static flow check Close the SSBOP Conventional well-control response is limited by the design and operating philosophy of conventional well-control technology. The challenges associated with these constraints include a significant drop in bottomhole pressure (BHP), increased influx volume before the well is finally secured, and the amount of time needed to detect an influx. The initial confirmation of an influx can take a substantial period of time because of a variety of factors that can influence the return flow rate and mud-pit volumes. On a deepwater rig, the interpretation of pit-volume and flow-rate changes can be subjective. To complicate matters further, conventional drilling rigs often are equipped only with inaccurate paddle flowmeters on the main flowline to measure flow out of the well; these do not offer a precise flow measurement. The conventional well-control-response procedure does not seem adequate for the deepwater drilling environment when evaluated in terms of influx detection and response time, total influx volume, and reservoir drawdown. Furthermore, after the SSBOP is closed, the conventional well-control response is subject to significant residual risks in the form of stuck pipe, lost circulation from chokeline friction, and the exceeding of kick tolerance. Finally, closing the SSBOP does not address an influx that has been circulated into the riser undetected.

Real-Time Condition and Performance Monitoring of a Subsea Blowout Preventer Pipe Ram

Summary Presented here is a case study on the condition and performance monitoring (CPM) of a subsea blowout preventer (BOP) pipe ram. The proposed real-time CPM solution uses adaptive physics-based models that process sensor measurements at the point of origin (known as edge analytics). The adapted model coefficients are treated as a vector, the magnitude of which estimates the degree of health degradation and the phase of which identifies its source. The benefits of using an adaptive model-based approach over traditional machine-based learning and artificial-neural-networks solutions include zero algorithm-training times, broad applicability to BOPs, model modularity, and accurate health-degradation estimates. The proposed CPM methodology is validated on a BOP pipe ram using both operational and simulated data. A sensitivity study of the method to system uncertainty is also presented.

Risk analysis of subsea blowout preventer by mapping GO models into Bayesian networks

Bayesian network (BN) is commonly used in probabilistic risk quantification due to its powerful capacity in uncertain knowledge representation and uncertainty reasoning. For the formalization of BN models, this paper presents a novel approach on constructing a BN from GO model. The equivalent BNs of the seventeen basic operators in GO methodology are developed. Therefore, the existing GO model can be mapped into an equivalent BN on basis of these developed BNs of the operators. Subsea blowout preventer (BOP) system plays an important role in providing safety during the subsea drilling activities. A case of closing the subsea BOP in the presence of pump failures is used to illustrate the mapping process. First, its GO model is presented according to the flow chart of the case. Then, BN is obtained based on the presented GO model. The developed BN relaxes the limitations of GO model and is capable of probability updating and probability adapting. Sensitivity analysis is performed to find the key influencing factor. The three-axiom-based analysis method is used to validate the developed BN.

Development of 3000 m Subsea Blowout Preventer Experimental Prototype

A subsea blowout preventer experimental prototype is developed to meet the requirement of training operators, and the prototype consists of hydraulic control system, electronic control system and small-sized blowout preventer stack. Both the hydraulic control system and the electronic system are dual-mode redundant systems. Each system works independently and is switchable when there are any malfunctions. And it significantly improves the operation reliability of the equipment.

Performance analysis for subsea blind shear ram preventers subject to testing strategies

In a subsea blowout preventer system, a subsea blind shear ram preventer (BSRP) plays as a crucial safety barrier by cutting off the drill pipe and sealing the wellhead to prevent serious accidents. Testing and repairs of BSRPs are the main issues in operation and maintenance activities. It is important to assess BSRPs unavailability during proof and partial testing phases in order to ensure their safety functions. This paper presents a newly state-based approach for unavailability analysis by incorporating testing activities of BSRPs into multiphase Markov process. In the approach, states waiting for repair are taken into consideration. Analytical formulas for evaluation of time-dependent unavailability and average unavailability for BSRPs are developed. In addition, the non-periodic characteristics and effects of degradation are also taken into account in proof testing. The effects of testing errors and postponed repairs on the tendency of unavailability in partial testing phases are checked in the proposed models. Performance analyses for BSRPs configurations, scenarios and cases considered in the paper are carried out to demonstrate the application of the proposed models. Monte Carlo models for both proof and partial testing are developed and simulated. Different comparisons are performed for validation of the set of the derived formulations.

Reliability analysis of multiplex control system of subsea blowout preventer based on stochastic Petri net

Reliability analysis of multiplex control system of subsea blowout preventer based on stochastic Petri net

Risk-Based Verification of Subsea Blowout Preventer System

An enquiry into the Piper Alpha disaster in 1998 led to a new approach of goal setting safety legislation which forms the framework adopted by offshore regulators especially United Kingdom, to address and manage risks of Major Accident Hazards (MAH). This enhanced the concept of verification in general and Risk Based Verification (RBV) in particular. This paper presents the application of this concept of verification to the Blowout Preventer (BOP) which undoubtedly is the final line of defense against major accident of a blowout in offshore drilling for the management of MAHs. This research begins with a review of current trends in offshore safety regulations, a discussion on the concept of verification principles, benefits and RBV. A RBV framework is proposed for the management of hazards in a blowout preventer system. The BOP system is adequately explained followed by a demonstration of the applicability of proposed framework on the system with major accident hazards and Safety critical elements (SCEs) listed. The blind shear ram was found to be the most critical component i.e. SCE in the BOP system which is very much in line with the requirement for the verification of a shear rams. Finally, both the benefits and the limitations of RBV in offshore applications are highlighted

An imperfect maintenance policy for mission-oriented systems subject to degradation and external shocks

This paper develops a maintenance model for mission-oriented systems subject to natural degradation and external shocks. For mission-oriented systems which are used to perform safety-critical tasks, maintenance actions need to satisfy a range of constraints such as availability/reliability, maintenance duration and the opportunity of maintenance. Additionally, in developing maintenance policy, one needs to consider the natural degradation due to aging and wearing along with the external shocks due to variations of the operating environment. In this paper, the natural degradation is modeled as a Wiener process and the arrival of random shock as a homogeneous Poisson process. The damage caused by shocks is integrated into the degradation process, according to the cumulative shock model. Improvement factor model is used to characterize the impact of maintenance actions on system restoration. Optimal maintenance policy is obtained by minimizing the long-run cost rate. Finally, an example of subsea blowout preventer system is presented to illustrate the effectiveness of the proposed model.

Use of hazardous event frequency to evaluate safety integrity level of subsea blowout preventer

Generally, the Safety Integrity Level (SIL) of a subsea Blowout Preventer (BOP) is evaluated by determining the Probability of Failure on Demand (PFD), a low demand mode evaluation indicator. However, some SIL results are above the PFD's effective area despite the subsea BOP's demand rate being within the PFD's effective range. Determining a Hazardous Event Frequency (HEF) that can cover all demand rates could be useful when establishing the effective BOP SIL. This study focused on subsea BOP functions that follow guideline 070 of the Norwegian Oil and Gas. Events that control subsea well kicks are defined. The HEF of each BOP function is analyzed and compared with the PFD by investigating the frequency for each event and the demand rate for the components. In addition, risk control options related to PFD and HEF improvements are compared, and the effectiveness of HEF as a SIL verification for subsea BOP is assessed.

Dynamic Bayesian network modeling of reliability of subsea blowout preventer stack in presence of common cause failures

A subsea blowout preventer (BOP) stack is used to seal, control and monitor oil and gas wells. It can be regarded as a series–parallel system consisting of several subsystems. This paper develops the dynamic Bayesian network (DBN) of a parallel system with n components, taking account of common cause failures and imperfect coverage. Multiple error shock model is used to model common cause failures. Based on the proposed generic model, DBNs of the two commonly used stack types, namely the conventional BOP and modern BOP are developed. In order to evaluate the effects of the failure rates and coverage factor on the reliability and availability of the stacks, sensitivity analysis is performed.

Technology Focus: Deepwater Projects (May 2015)

Technology Focus As the oil and gas industry pushes into deeper water, more-complex environments, and frontier unproduced areas, the technical and nontechnical risks related to appraisal and development of deepwater projects are likely to continue to increase substantially. While the technical challenges related to deepwater developments are significant— perhaps more significant and critical to the venture success—it is important that the nontechnical aspects of managing a new development in a frontier area be incorporated at the onset. After the successful discoveries in deepwater basins across the globe in west Africa, the North Sea, the Gulf of Mexico, Brazil, and elsewhere, operators are using the lessons learned and technologies developed in these fields to explore other frontier deepwater fields. The exploration in deep water becomes complex on the basis of various factors, such as water depth, geological formations, weather conditions, lack of oilfield infrastructure, and material and tools availability. The definition of deep water may vary with operators, but one definition of a deepwater field is any area of exploration where the water depth is greater than 150 m and there is a subsea blowout preventer. NORSOK defines deep water as water depth in excess of 600 m. Deep water may range from 600 to 3000 m, and ultradeep water is anything deeper than that. Deepwater operations create several additional challenges that need to be addressed in the design phase. Some of these, such as low temperatures at seabed, shallow flow hazards, and possible hydrates, are problems that are most commonly associated with deepwater operations. Other challenges, such as low fracture gradients and proper mud removal for cement placement and zonal isolation, are also common in nondeepwater environments; however, these become more complex, more significant, and more difficult to manage in deep water. There is no question that deepwater production will play a very important part in meeting the world’s future energy demand. The challenge for the oil and gas industry is to meet this demand safely, efficiently, and profitably. This is not an easy challenge in deep water, given the limited margin for error. The technical complexity and multibillion-dollar development costs require a robust development strategy that allows a project to deliver the promised value within the constraints of time. JPT Recommended additional reading at OnePetro: www.onepetro.org. OTC 25135 Deepwater Development Strategy by Martijn Dekker, Shell, et al. OTC 25443 50 Reservoirs, 48 Well Slots, and Two TLPs—Maximizing Recovery From the Deepwater Prolific Mars Field by Derek Newberry, Shell SPE 169245 Overcoming Ultradeepwater Cementing Challenges.in.the Caribbean by N. Gupta,_Schlumberger, et al. SPE 170286 A Novel Approach in Locating Single Loss Zone During Deepwater Drilling With Distributed- Temperature Measurement by Yuanhang Chen, The University of Tulsa, et al.

Availability analysis of subsea blowout preventer using Markov model considering demand rate

Availabilities of subsea Blowout Preventers (BOP) in the Gulf of Mexico Outer Continental Shelf (GoM OCS) is investigated using a Markov method. An updated β factor model by SINTEF is used for common-cause failures in multiple redundant systems. Coefficient values of failure rates for the Markov model are derived using the β factor model of the PDS (reliability of computer-based safety systems, Norwegian acronym) method. The blind shear ram preventer system of the subsea BOP components considers a demand rate to reflect reality more. Markov models considering the demand rate for one or two components are introduced. Two data sets are compared at the GoM OCS. The results show that three or four pipe ram preventers give similar availabilities, but redundant blind shear ram preventers or annular preventers enhance the availability of the subsea BOP. Also control systems (PODs) and connectors are contributable components to improve the availability of the subsea BOPs based on sensitivity analysis.

Reliability analysis of the electrical control system of subsea blowout preventers using Markov models.

Reliability analysis of the electrical control system of a subsea blowout preventer (BOP) stack is carried out based on Markov method. For the subsea BOP electrical control system used in the current work, the 3-2-1-0 and 3-2-0 input voting schemes are available. The effects of the voting schemes on system performance are evaluated based on Markov models. In addition, the effects of failure rates of the modules and repair time on system reliability indices are also investigated.

Application of Petri nets to performance evaluation of subsea blowout preventer system

This paper presents an application of deterministic and stochastic Petri nets (DSPN) to evaluate the performance of subsea blowout preventer (BOP) system. The overall subsea BOP system is comprised of five mechanical subsystems and five electrical subsystems, which can be viewed as a series-parallel system. In regard to common cause failures, TimeNET 4.0 toolkit is utilized to develop and analyze the DSPN models. Availability and reliability of the subsea BOP system and its subsystems are obtained. Besides, the effects of failure rate and repair time of each component on system performance are researched.