collected, calculated, or monitored
during operations to improve the current
level of safety. Identify any existing or
proposed modeling tools that can be
used in connection with real-time data to
prevent incidents
Chapter Summary
As the industry is pushed into more complex exploration and production environments, more complex tools and technology are necessary to allow safe recovery of hydrocarbons. This paper explores the current information available for deep water operators in the Gulf of Mexico (GOM) and what additional information might be necessary to improve the levels of safety during exploration and production.
On newer rigs, increasingly sophisticated sensors are delivering enormous volume of data that is being harnessed to generate more efficient well delivery and production. To best take advantage of this valuable asset, new work processes are being developed and revised on a daily basis to utilize the data. The organizations striving to be successful have adopted these advances and aggregated the data streams into real-time operations centers and collaboration centers offering real-time monitoring of day to day operations. These centers provide centralized collaboration and communication; and highly skilled expertise for creating safe operations. The aggregation and organization of the data is extremely important to all parts of the exploration and production process. In this enterprise, third party vendors offer many commercially available and custom solutions to formulate coherent information for well optimization and event monitoring. But regardless of the sophistication of the data analysis operation, the data is only as good as the sensors, and considering ever increasingly complex operations, the
development and adoption of advanced measurement systems and sensors producing the data are lagging behind the requirement to produce what is fast becoming a near zero acceptable risk tolerance for well delivery and production. The rigs operating in the GOM today range in age from brand new to over thirty years and the sensor systems aboard vary just as greatly. Generally, these sensors provide data from drilling and performance equipment which measure how the well is being delivered; lithology data which encompasses wellbore data; and information on the condition and wear of equipment to determine service and repair interventions.33 The industry needs to embrace methods of continuous and direct measurement of well control parameters and not be satisfied with the status quo of intermittent and surface measurements that provide data requiring highly experienced drillers to infer downhole situations. These measurement changes will offer a marked decrease in the risk factor of operating deepwater well and a corresponding improvement in safety.
However, improving the technical aspect of well delivery and production is only half of the safety improvement equation. Improving the human element is the other half. People make mistakes. Human error is cited as a contributing factor in the majority (up to 80%) of industrial accidents and incidents.31 The key to decreasing risk and improving safety requires continuous learning from the mistakes of others as well as our own. The
aviation industry has embraced the study of the human factors side of accidents and uses it as a basis for training and safety improvements. The Human Factors Analysis and Classification System (HFACS) is a framework used to identify and classify the human data element thereby providing an avenue for improving human interaction with technology and painting a holistic approach to improved safety.
HFACS is based on James Reason’s model of latent and active failures, the ‘Swiss cheese’ model. The oil and gas HFACS framework has been adapted from the aviation industry and provides a common framework to systematically classify accident and incident contributing factors. Errors, incidents and accidents are analyzed for their root causes and categorized in the HFACS nanocodes permitting further analysis for organizational trending allowing for systematic improvements to identified problem areas and avenues for predictive analysis of the human element.
Proactively avoiding errors, incidents or accidents, with improved training can have a significant impact on safety. With advanced computing power and developments in the gaming industry, oil and gas industry engineers can now visualize the well planning process. 3D modeling and simulation enables all relevant parties to come together using common databases and common professional languages, pooling resources for the project. The efficiencies gained by these enhanced planning tools inherently
plays directly into improved safety margins. The industry is also seeing a rise in Human in the Loop (HITL) simulation allowing for increased experience levels and practiced procedures prior to ever being on the rig. The use of Crew Resource Management (CRM) tools is a necessary addition to these training methods.
Every new well drilled represents new and different challenges than all previous wells. With advancing technologies and new processes becoming available almost daily, operators must accept that new drilling standards are necessary and required for safe operations in the Outer Continental Shelf (OCS) Gulf of Mexico in order to mitigate risk factors in today’s ‘critical’ and extremely challenging well scenarios. Updating measurement, collection and monitoring systems to BAST (Best Available and Safest Technology) for the technical and human data elements along with advanced, predictive analysis open the window for improving the safety culture of the industry and lowering acceptable risk tolerance.
Introduction
The use of drill string measurements and basic sensor data has long been the key to informing the drilling process and maintaining well control within acceptable safety margins. In December 1937, time- based analog charts were introduced with the Geolograph as a basic tool for trend analysis and identification of anomalies. This invention quickly became the de-facto method for keeping a record of events.1 The transistor’s introduction in 1947 brought about another step change in well monitoring with the introduction of sensor capabilities. In the early 1970’s, the oil and gas industry entered a new era by employing digital analytics throughout the exploration and production chain providing a wealth of new information about the condition of the well. The relatively low data rates at the time made for a manageable solution, but the limited information only provided part of the well environment picture.
The introduction of measurement-while- drilling (MWD) and logging-while-drilling (LWD) has enhanced the downhole picture from wireline technology bringing this data to near real-time, but low downhole data rates limited by bandwidth remain a barrier to a truly revolutionary breakthrough in real- time data and analysis of the downhole picture.
The question for this paper requires outlining the information necessary from the well site to improve margins of safety during exploration and production. Keeping within this scope, this paper will explore those data
sets and information directly related to improved safety without regard for data considerations for improvements in Non- Productive Time (NPT) and other efficiencies in the exploration and production processes.
The assumption should not be made that having this data or mandating its collection will inherently make the project safer. Appropriate analysis, experience and recognition are necessary to transform data into usable information for the purposes of improving margins of safety. Many of the leading operators have pooled this information in collaboration centers where the data is processed in real-time or analyzed post-process to provide enhanced business solutions and increased operating safety margins.
The industry has moved years and technological generations beyond simple mud logging. The aggregation of rig sensor data, accompanied with real-time and post- processing analysis, delivers enhanced
Task 4: Identify all necessary information which needs to be collected, calculated, or monitored during operations to improve the current level of safety. Data should include, but is not limited to, pressure drops, fluid influx, fluid loss, and the operation of BOP functions. Identify any existing or proposed modeling tools that can be used in connection with real-time data to prevent incidents.
levels of production, reduced NPT and with it, improved operating safety margins. The technical advances and enhanced data only provide part of the palette necessary to paint the safety improvement picture. The human element plays a huge role and in effect is the most susceptible to failure in the dynamic environment of the oil and gas industry. Human error is cited as a contributing factor in the majority (up to 80%) of industrial accidents and incidents.31 The Human Factors Analysis and Classification System (HFACS) framework provides a common framework to systematically classify accident contributing factors and is the basis for continuous improvement of the human element in the safety equation. HFACS originates from the aviation industry and is based on James Reason’s model of latent and active failures, the ‘Swiss cheese’ model.
And just as HFACS can lead future advancements in safety, advanced training programs can stop accidents before they happen. Gaming industry technology and advancing computing power have changed the well planning process. The addition of 3D modeling and simulation enables all relevant parties to come together using common databases and common professional languages. The efficiencies gained by these enhanced planning tools inherently plays directly into improved safety margins.
Use of human in the loop (HITL) simulation is also on the rise promoting increased experience levels and practiced procedures prior to ever being on the rig. The use of
crew resource management (CRM) tools is a necessary addition to these training methods.
This paper explores collection methods, data calculation and monitoring requirements during operations for both the technical and human aspect of the safety equation. We also explore the technology currently used to acquire data and potential improvements in collection, monitoring and calculation of data ensuring a safer operating environment.
Information to Improve Levels of Safety
Data collection and organization
The collection of data is only the beginning of the process to improve industry safety levels. The collected data must be organized, analyzed and presented to enable an accurate decision which will result in improved levels of safety.
Drilling industry operations primarily produce three parallel data flows that occur with varying degrees of interdependency. The first data stream includes all data collected for drilling and performance which measures and describes how the well is being delivered. This data is usually acquired by multiple third party contractors from sensors throughout the rig, downhole and at times, in a manually written format. The second data stream can be generally classified as lithology data and encompasses wellbore data measured continuously and intermittently by service providers. Data is acquired by specialized sensors through surface and downhole tools and is used to update the subsurface model.
The third data stream is usually acquired by the Rig contractor and provides information on the condition and wear of equipment to determine service and repair interventions.33 The amount of data streaming from the rig continues to grow with new technological advancement. To utilize this data the industry has been slowly embracing the use of collaboration centers which provide handling and analysis. The collaboration
centers are generally organized to use real- time streaming data or may analyze data previously collected.
Five common success factors have been observed in established collaboration centers that have demonstrated reliability and/or performance improvements:
Environment - Putting equipment operating condition into context. Equipment operating in a dynamic environment, under a range of conditions requires data to be collected and referenced with respect to the conditions encountered during the evaluated timeframe.
Data - Collecting and managing data by exception. The blizzard of data now available requires machine learning and management by exception to reduce data into usable information.
Analysis - Using both predictive analytics and deep diagnostics as complementary technologies that operate in different timeframes. Deep diagnostics may include such things as vibration signature analysis and cylinder performance analysis, while predictive analytics employs pattern recognition algorithms to detect minor events and anomalies.
Cooperation – Industry wide
communication of observations, diagnoses, recommendations and lessons learned through collaboration tools. Such tools add value on multiple fronts that include knowledge transfer and equipment-specific learning such as Root Cause Analysis.
Management - Managing the findings in a knowledge-management system or collaboration system. This provides feedback for further improvement.
Collaboration centers utilizing these factors have been able to successfully meld the parameter data into a relatively accurate picture of the downhole environment allowing them to operate within an enlarged safety envelope.
Collected Data
The oil and gas industry operates in extreme conditions and encounters many types and ranges of physical conditions that can and should be measured. In conventional operations, drilling engineers track various operational parameters such as pressure, flow, torque, temperature and others. These parameters provide only a simple picture of the behavior of the drill string bottom hole assembly (BHA) and well condition. Typically, a driller will use this limited operational information, his experience and a few rules of thumb to manage drilling operations in the most efficient and safest manner possible.
In addition to these traditional tools, dynamically derived data can be useful for providing a clearer picture of the exploration and production processes. Measurements of these parameters provide the necessary data to properly control the well during exploration and production.34 A comprehensive, but not exhaustive list of measured parameters that should be collected for operating conditions in well operations includes:
Pressure
The measurement of pressure is complicated by the wide range of requirements from small variations to large pulses. Quartz resonator technology currently dominates the single point sensor market for pressure. Pressure sensing is used throughout the industry to indicate performance and to act as an alarm to an unsafe condition. Important pressures to track include:
fluid pressure
hydrostatic pressure
formation pressure
fracture pressure
bottom hole pressure
Each of these pressures plays a key role in well control.
Hydraulic
Hydraulic measurements involve constant monitoring and analysis of flow, flow rate, density and rheology of the drilling fluid. Flow of a fluid is performed based on the principle of a Venturi. The Venturi has two pressure sensors that measure pressure before and after the Venturi device. The measurement of flow is particularly important to drilling operations for ensuring proper flow of mud and pipeline monitoring for oil and natural gas. Flow can also be measured by counting pump strokes and applying an efficiency factor and through acoustic measurement devices. Coriolis meters continuously measure mass flow rate (density of the mud and the rate it is flowing).33 Mud density and flow properties
are also measured by a fann viscometer and others offering real- time density and viscosity measurements.
Torque
The measurement of torque is one of the most important parts of drilling a well. Historically, the torque meter has been an unusually large dial in prominent view of all personnel on the rig deck. The necessary torque applied to the drill string by the rotary table or top drive tells the driller much information about the formation through which he is drilling and stresses placed on the drill stem. Weight on bit changes, Rate of Penetration (ROP), formation transitions and stick/slip situations cause noticeable variations and/or spikes in torque as displayed on the torque meter. This alerts crews to drill stem anomalies or changing bit dynamics causing potential hazards to drilling operations. A spike in torque exceeding drill string limits will likely damage equipment and could cause injuries.
Tension
The simple force on a strain gauge is used to report tension. It is important to know the tension on riser tensioners and on mooring lines used for station keeping of floating drilling rigs and structures. Additional uses include measuring tension and compression to avoid damage to the logging tools and detecting strain on cables. Tensions measurements provide logging engineers with early indications of over-pull, tool drag, stuck tools, tool compression, and irregular tool movement.
Temperature
The extremes of temperature mirror those of pressure. Subsequently, there are many sensors that perform both functions. Quartz resonator technology currently dominates the single point sensor market for temperature. Temperature sensing is used throughout the industry and important when safe limits are exceeded for a desired operation or when there are changing conditions for fluids and pressures.
Chemical Composition
The chemical composition of the substances in the oil and gas industry is wide and varied. It is important to know the composition to be able to judge the environment for hazardous substances, flammability, consistency, density and other properties of oil, natural gas, and mud. The products going down the well need as much attention as the products coming up the well. It is critical to safety to sense the gas composition of the fluids in the well by sensing for gases such as Hydrogen Sulfide (H2S).
Vibration
When drilling operations are underway it seems that vibration is in every part of the rig. There are limits to the vibration that certain pieces of equipment will sustain. An unexpected change in vibration can be a sign of impending failure. The vibration is measured with some of the same technology that is used to measure pressure.
Weight
Weight on bit, drill stem, and casing is critical to measure properly to assess the work being performed by the drill bit. The proper weight on bit is a balancing act that requires a constant vigil. It is an important parameter that is reported alongside the torque applied to the drill stem. Important aspects include setting/releasing mechanical set tools, indications of hanging up / restriction while tripping, and indications of amount of overpull applied.
Position
Current position and position change are necessary to ensure the intended geographic location is maintained or is attained. The location of the drill ship during drilling operations is paramount. The position can be reported in conjunction with the tension on mooring lines to anticipate movement of the vessel. Engines and thrusters are also monitored and controlled. Buoys can provide wave height by simple measurements of inertial energy. The position of the drill bit is the prime objective and must be monitored constantly. A change in position can be compared against time to produces a rate of change. Directing the position of the bottom hole assembly is also important for directional drilling where MWD tools have proven invaluable for guiding the directional drilling process.
Seismic
The use of seismic sensors has utility in the detection of production fields that contain enough valuable products to warrant exploration. Seismic sensors use the same
technology as vibration sensors. They are generally deployed over a large area to gain insight to the capability of the rock strata to produce product by returning different frequencies based upon the composition of the material and the propagation of sound through different media. The vibration of the drill string and the equipment connected to the well are sensed by the toolpusher and are a valuable tool for detecting problems.