Well control and blowout prevention have become particularly important topics in the hydrocarbon production industry for many reasons. Among these reasons are higher drilling costs, waste of natural resources, and the possible loss of human life when kicks and blowouts occur. One concern is the increasing number of governmental regulations and restrictions placed on the hydrocarbon industry, partially as a result of recent, much-publicized well-control incidents. For these and other reasons, it is important that drilling personnel understand well-control principles and the procedures to follow to properly control potential blowouts. Many well-control procedures have been developed over the years.
What Has Been the Industry's Experience Over the Past 10 Years? Why Have Barriers Failed in Well Control Situations? Many well control incidents are either directly or indirectly related to barrier failure. The historical consequence has in a few cases been significant and shaped public perception of the industry. Loss of life, significant injury, and negative environmental impact are unacceptable; the industry must get barrier management right every time.
The yet to be developed Liberty field was discovered in the 1980s, and then confirmed with the Liberty No. 1 well in 1997 by BP Exploration Alaska, Inc. (BPXA). The Liberty reservoir lies within the Outer Continental Shelf (OCS) in approximately 20′ of water, in Foggy Island Bay, about 20 miles ESE of Prudhoe Bay field. The reservoir is estimated to contain between 80 and 140 MMBO of reserves. In 2014, Hilcorp Alaska, LLC (Hilcorp) purchased 50% ownership and assumed operatorship from BPXA, and submitted the Development and Production Plan (DPP) to the Bureau of Ocean Energy Management (BOEM). Since then, BOEM as the lead agency, has been conducting a National Environmental Protection Act (NEPA) review which is expected to deliver the Final Environmental Impact Statement (EIS) in mid-2018.
Concurrent with the NEPA review, Hilcorp submitted the Oil Spill Response Plan (OSRP) to BSEE in March 2017. A unique feature of this development in OCS waters is that wells will be drilled from an artificial gravel island using a land-based rig. One of the key elements of the OSRP is the utilization of well ignition as an early step in a well capping operation which subsequently minimizes the volume of oil that hits the ocean or ice if a well were to blowout. As prescribed in regulations, the operator must demonstrate it has a plan and resources to remediate a spill of the worst case discharge (WCD) rate. Because the Kekiktuk formation at Liberty has very high (>1 darcy) permeability, the initial WCD rate of a blowout from the full exposure to the reservoir and up 9-5/8″ casing is approximately 91,000 bopd and 84 MMscfpd.
To prove the WCD rate would remain ignited, and to calculate the percent of liquid that would combust, first BPXA then Hilcorp, hired two companies, Boots & Coots Inc. with Intuitive Machines, LLC. to: research the robustness of combustion models; develop models that would determine if the blowout would remain ignited; and, to calculate the liquid carryover that would have to be recovered with spill response equipment. The companies created several models that resolved these issues, including: 1) burn efficiency, defined as the ratio of oil combusted to total oil exiting wellbore, 2) blowout flame radiant heat flux, 3) mass flux and heat content of unburned residual, and, 4) spatial distribution of unburned residual. The work was based on four broad areas: 1) research of governing physics, 2) evaluation of academic and laboratory scale measurements, 3) evaluation of a blowout database, and, 4) numerical modeling utilizing both computational fluid dynamics and first principles engineering modeling. The numerical model validated the presence of complex supersonic shock structures and calibration data for the development of the engineering burn efficiency methodology. Research results were integrated with extensive field-based blowout experience and validated numerical modeling results. Parametric analysis of key driving variables provide measures of burn efficiency margin and robustness required for approval of the OSRP.
This paper presents the methodology and engineering-based solution that integrates oil blowout fire experience with aerospace engineering expertise to adequately and accurately predict burn efficiency of high rate blowouts. This methodology allows the operator to justify the use of well ignition as a step in well capping and as a means of source control, on a new field development from an artificial gravel island in the Beaufort Sea, in Arctic OCS waters.
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Commonly, the Managed Pressure / UnderBalanced Drilling (MP/UB) detailed engineering is focused on operation design based on Well expected conditions and/or correlation data, its primordial objective is to provide operational guidelines and means to properly deal when facing unplanned events and improve drilling safety and efficiency while performing MP/UB.
Due to highly abnormal pore pressure observed in Block A South phase I development, several unexpected problems were encountered. Well targeting, operation and integrity issues were studied to minimize in the next phase of Block A South development. Phase II well designs were renewed to gain reservoir optimization. This paper presents the field mitigation and operational improvement of Block A South development from phase I to II, and the proposed guideline to later Block A South phases. For instance, Block A South phase III is another achievement to perform on these development strategies.
Block A South comprises many reservoir sections from shallow target – 2E unit, down to deep target – FM1. Pore pressure starts to ramp up at lower 2D unit and back to normal pressure at lower 2A unit. All targets were combined in a single well for reservoir maximization in phase I. However, it caused problems in terms of well operation and integrity during production. Therefore, new well design was planned to segregate reservoir targets as shallow, intermediate and deep sections to minimize operational issues. These three types of new well designs were also incorporated with pressure pregnant profiles. After two batches of fifteen wells drilled in Platform A, many operation issues, well control, borehole collapse and well integrity, were experienced. Average well cost was approximately 30 percent in excess of plan. Only half of drilled wells cannot be put on stream as planned due to cementing and integrity problems.
For Block A South phase II, pressure prediction is precisely conscious to avoid operational problems. Platform H was first developed with abnormal pressure of 1.65 sg. The new designs show success in the platform development. The Platform H new well drilling gives rise to about 20% increase in success rate from Platform A drilling. Also, average well cost is as planned. Platform G, which investigates maximum observed pressure up to 1.85 sg, exhibited all methods to avoid operational problems. 85% of wells drilled in Platform G have no problems and average well cost is within 5 percent exceeding plan. Actual operation cost and time yield better results than expected. Additionally, larger amount of volume in Platform G has been produced comparing to Platform A. The overall result of Platform G is favorable to the next phase of Block A South development.
The strategies are acceptable results to control operation with abnormal pressure. It is beneficial to Block A South development and investment. Lesson learned from these practices will provide operational improvement in later Block A South phase. These designs can be applied to other fields in the Gulf of Thailand.
Many well control incidents have been analyzed, resulting in the optimum practices, as outlined in this paper. The objective of this paper is to propose a set of guidelines for the optimal well control operations, by integrating current best practices through a decision-making system based on Artificial Bayesian Intelligence.
Best well control practices collected from data, models, and experts' opinions, are integrated into a Bayesian Network to simulate likely scenarios of its use that will honor efficient practices. When dictated by varying operation, kick details, and kick severity. The proposed decision-making model follows a causal and an uncertainty-based approach capable of simulating realistic conditions on the use of well control operations. For instance, by varying the operation, the system will show the kick indicators for that particular operation. Also in the same model as the user vary the operation, rig and crew capabilities, kick details (such as slim hole, deviated or horizontal well), the system will show the optimum practices for circulation method and shut in method. The model also shows optimum practices for blowout control by varying the un-controlled kick type (surface, subsurface or underground blowouts). Recommended practices after controlling the well are shown by the same operation that caused the well control incident and by varying the potential reason for the incident.
Two well control experts' opinions were considered in building up the model in this paper. The advantage of the artificial Bayesian intelligence method is that it can be updated easily when dealing with different opinions. The outcome of this paper is user-friendly software, where you can easily find the specific subject of interest, and by the click of a button, get the related information you are seeking. Field cases will also be discussed to validate this work.
Many well control incidents have been analyzed, resulting in the optimumpractices, as outlined in this paper. To the best of the authors' knowledge,there are no systematic guidelines for well control practices. The objective ofthis paper is to propose a set of guidelines for the optimal well controloperations, by integrating current best practices through a decision-makingsystem based on Artificial Bayesian Intelligence. Best well control practicescollected from data, models, and experts' opinions, are integrated into aBayesian Network BN to simulate likely scenarios of its use that will honorefficient practices
when dictated by varying operation, kick details, and kick severity.
The proposed decision-making model follows a causal and an uncertainty-basedapproach capable of simulating realistic conditions on the use of well controloperations. For instance, as the user vary the operation, rig and crewcapabilities, kick details (such as slim hole, deviated or horizontal well),the system will show the optimum practices for circulation method.
Well control experts' opinions were considered in building up the model in thispaper. The advantage of the artificial Bayesian intelligence method is that itcan be updated easily when dealing with different opinions. The outcome of thispaper is user-friendly software, where you can easily find the specific subjectof interest, and by the click of a button, get the related information you areseeking.
Technology Focus - No abstract available.
In the last 25 years, we have witnessed the introduction of technology that is nothing short of astonishing--things that most of us would never have imagined during our early days in the field and on the rigs. Today, we have the ability to look at a computer screen that provides a virtually instantaneous reading of numerous downhole parameters (e.g., annular pressure near the bit, equivalent circulating density, temperature, torque, vibration, and lithology). Advances in surface monitoring have lead to significant improvements in computerized displays of pressures, rates, and volumes, all of which are crucial to maintaining hydrostatic control of the well. Some may wonder how wells were ever drilled without these high-tech tools. In December 1982, there were 4,530 rigs running in the US vs. approximately 1,800 rigs running in the US today.