scholarly journals Application of a Drilling Simulator for Real-Time Drilling Hydraulics Training and Research

2021 ◽  
Author(s):  
Jelena Skenderija ◽  
Alexis Koulidis ◽  
Vassilios Kelessidis ◽  
Shehab Ahmed
Keyword(s):  
Real Time ◽  
Field Data ◽  
Drilling Fluid ◽  
Fluid Pressure ◽  
Drilling Process ◽  
Rheological Models ◽  
Pressure Losses ◽  
Drilling Parameters ◽  
Wellbore Pressure ◽  
Actual Field

Abstract Challenging wells require an accurate hydraulic model to achieve maximum performance for drilling applications. This work was conducted with a simulator capable of recreating the actual drilling process, including on-the-fly adjustments of the drilling parameters. The paper focuses on the predictions of the drilling simulator's pressure losses inside the drill string and across the open-hole and casing annuli applying the most common rheological models. Comparison is then made with pressure losses from field data. Drilling data of vertical and deviated wells were acquired to recreate the actual drilling environment and wellbore design. Several sections with a variety of wellbore sizes were simulated in order to observe the response of the various rheological models. The simulator allows the input of wellbore and bottom-hole assembly (BHA) sizes, formation properties, drilling parameters, and drilling fluid properties. To assess the hydraulic model's performance during drilling, the user is required to input the drilling parameters based on field data and match the penetration rate. The resulting simulator hydraulic outputs are the equivalent circulation density (ECD) and standpipe pressure (SPP). The simulator's performance was assessed using separate simulations with different rheological models and compared with actual field data. Similarities, differences, and potential improvements were then reported. During the simulation, the most critical drilling parameters are displayed, emulating real-time measured values, combined with the pore pressure, wellbore pressure, and fracture pressure graphs. The simulation results show promise for application of real-time hydraulic operations. The simulated output parameters, ECD and SPP, have similar trends and values with the values from actual field data. The simulator's performance shows excellent matching for a simple BHA, with decreasing system's accuracy as the BHA design becomes more complex, an area of future improvement. The overall approach is valid for non-Newtonian drilling fluid pressure losses. The user can observe the output parameters, and by adding a benchmark safety value, the simulator gives a warning of a potential fracture of the formation or maximum pressure at the mud pumps. Thus, by simulating the drilling process, the user can be trained for the upcoming drilling campaign and reach the target depth safely and cost-effectively during actual drilling. The simulator allows emulation of real-time hydraulic operations when drilling vertical and directional wells, albeit with a simple BHA for the latter. The user can instantly observe the output results, which allows proper action to be taken if necessary. This is a step towards real-time hydraulic operations. The results also indicate that the simulator can be used as an excellent training tool for professionals and students by creating wellbore exercises that can cover different operating scenarios.

scholarly journals Application of Artificial Intelligence Techniques in Predicting the Lost Circulation Zones Using Drilling Sensors

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Abdulmalek Ahmed ◽  
Salaheldin Elkatatny ◽  
Abdulwahab Ali ◽  
Mahmoud Abughaban ◽  
Abdulazeez Abdulraheem
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Drilling Fluid ◽  
Confusion Matrix ◽  
High Accuracy ◽  
Functional Networks ◽  
Lost Circulation ◽  
Drilling Parameters ◽  
High Pressure High Temperature ◽  
Drilling Cost

Drilling a high-pressure, high-temperature (HPHT) well involves many difficulties and challenges. One of the greatest difficulties is the loss of circulation. Almost 40% of the drilling cost is attributed to the drilling fluid, so the loss of the fluid considerably increases the total drilling cost. There are several approaches to avoid loss of return; one of these approaches is preventing the occurrence of the losses by identifying the lost circulation zones. Most of these approaches are difficult to apply due to some constraints in the field. The purpose of this work is to apply three artificial intelligence (AI) techniques, namely, functional networks (FN), artificial neural networks (ANN), and fuzzy logic (FL), to identify the lost circulation zones. Real-time surface drilling parameters of three wells were obtained using real-time drilling sensors. Well A was utilized for training and testing the three developed AI models, whereas Well B and Well C were utilized to validate them. High accuracy was achieved by the three AI models based on the root mean square error (RMSE), confusion matrix, and correlation coefficient (R). All the AI models identified the lost circulation zones in Well A with high accuracy where the R is more than 0.98 and RMSE is less than 0.09. ANN is the most accurate model with R=0.99 and RMSE=0.05. An ANN was able to predict the lost circulation zones in the unseen Well B and Well C with R=0.946 and RMSE=0.165 and R=0.952 and RMSE=0.155, respectively.

Usage of Geomechanically Consistent Fracture Model for Drilling Deviated Wells

2021 ◽  
Author(s):  
Nikita Vladislavovich Dubinya ◽  
Sergey Andreevich Tikhotskiy ◽  
Sergey Vladimirovich Fomichev ◽  
Sergey Vladimirovich Golovin
Keyword(s):  
Optimal Trajectory ◽  
Fractured Reservoirs ◽  
Fluid Pressure ◽  
Naturally Fractured Reservoirs ◽  
Natural Fracture ◽  
Fracture Model ◽  
Drilling Process ◽  
Natural Fractures ◽  
Drilling Parameters ◽  
Deviated Wells

Abstract The paper presents an algorithm for the search of the optimal frilling trajectory for a deviated well which is applicable for development of naturally fractured reservoirs. Criterion for identifying the optimal trajectory is the feature of the current study – optimal trajectory is chosen from the perspective of maximizing the positive effect related to activation of natural fractures in well surrounding rock masses caused by changes of the rocks stress-strain state due to drilling process. Drilling of a deviated well is shown to lead to the process of natural fractures in the vicinity of the well becoming hydraulically conductive due to drilling. The paper investigates the main natural factors – tectonic stresses and fluid pressure – and drilling parameters – drilling trajectory and mud pressure – influencing the number and variety of natural fractures being activated due to drilling process. An algorithm of finding the optimal drilling parameters from the perspective of natural fractures activation is proposed as well. Different theoretical scenarios are considered to formulate the general recommendations on drilling trajectory choice according to estimations of stress state of the reservoir. These estimations can be provided based on results of three- and four-dimensional geomechanical modeling. Such modeling may be completed as well for constructing geomechanically consistent natural fracture model which can be used to optimize drilling trajectories during exploration and development of certain objects. The paper presents a detailed algorithm of constructing such fracture models and deviated wells trajectories optimization. The results presented in the paper and given recommendations may be used to enhance drilling efficiency for reservoirs characterized by considerable contribution of natural fractures into filtration processes.

Case Studies for the Successful Deployment of Wells Augmented Stuck Pipe Indicator in Wells Real Time Centre

2021 ◽  
Author(s):  
Meor M. Meor Hashim ◽  
M. Hazwan Yusoff ◽  
M. Faris Arriffin ◽  
Azlan Mohamad ◽  
Tengku Ezharuddin Tengku Bidin ◽  
...  
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Drilling Fluid ◽  
Drill String ◽  
Drilling Operation ◽  
Cost Impact ◽  
Drilling Parameters ◽  
The Impact ◽  
Productive Time ◽  
Specific Challenge

Abstract The restriction or inability of the drill string to reciprocate or rotate while in the borehole is commonly known as a stuck pipe. This event is typically accompanied by constraints in drilling fluid flow, except for differential sticking. The stuck pipe can manifest based on three different mechanisms, i.e. pack-off, differential sticking, and wellbore geometry. Despite its infrequent occurrence, non-productive time (NPT) events have a massive cost impact. Nevertheless, stuck pipe incidents can be evaded with proper identification of its unique symptoms which allows an early intervention and remediation action. Over the decades, multiple analytical studies have been attempted to predict stuck pipe occurrences. The latest venture into this drilling operational challenge now utilizes Machine Learning (ML) algorithms in forecasting stuck pipe risk. An ML solution namely, Wells Augmented Stuck Pipe Indicator (WASP), is developed to tackle this specific challenge. The solution leverages on real-time drilling database and supplementary engineering design information to estimate proxy drilling parameters which provide active and impartial pattern recognition of prospective stuck pipe events. The solution is built to assist Wells Real Time Centre (WRTC) personnel in proactively providing a holistic perspective in anticipating potential anomalies and recommending remedial countermeasures before incidents happen. Several case studies are outlined to exhibit the impact of WASP in real-time drilling operation monitoring and intervention where WASP is capable to identify stuck pipe symptoms a few hours earlier and provide warnings for stuck pipe avoidance. The presented case studies were run on various live wells where restrictions are predicted stands ahead of the incidents. Warnings and alarms were generated, allowing further analysis by the personnel to verify and assess the situation before delivering a precautionary procedure to the rig site. The implementation of the WASP will reduce analysis time and provide timely prescriptive action in the proactive real-time drilling operation monitoring and intervention hub, subsequently creating value through cost containment and operational efficiency.

scholarly journals Exploitation of Field Drilling Data with an Innovative Drilling Simulator: Highly Effective Simulation of Rotating and Sliding Mode

2021 ◽  
Author(s):  
Alexis Koulidis ◽  
Vassilios Kelessidis ◽  
Shehab Ahmed
Keyword(s):  
Field Data ◽  
Sliding Mode ◽  
P Wave ◽  
Drilling Process ◽  
Continuous Change ◽  
Rate Of Penetration ◽  
Drilling Performance ◽  
Drilling Parameters ◽  
Rock Drillability ◽  
Drilling Data

Abstract Drilling challenging wells requires a combination of drilling analytics and comprehensive simulation to prevent poor drilling performance and avoid drilling issues for the upcoming drilling campaign. This work focuses on the capabilities of a drilling simulator that can simulate the directional drilling process with the use of actual field data for the training of students and professionals. This paper presents the results of simulating both rotating and sliding modes and successfully matching the rate of penetration and the trajectory of an S-type well. Monitored drilling data from the well were used to simulate the drilling process. These included weight on bit, revolutions per minute, flow rate, bit type, inclination and drilling fluid properties. The well was an S-type well with maximum inclination of 16 degrees. There were continuous variations from rotating to sliding mode, and the challenge was approached by classifying drilling data into intervals of 20 feet to obtain an appropriate resolution and efficient simulation. The simulator requires formation strength, pore and fracture pressures, and details of well lithology, thus simulating the actual drilling environment. The uniaxial compressive strength of the rock layer is calculated from p–wave velocity data from an offset field. Rock drillability is finally estimated as a function of the rock properties of the drilled layer, bit type and the values of the drilling parameters. It is then converted to rate of penetration and matched to actual data. Changes in the drilling parameters were followed as per the field data. The simulator reproduces the drilling process in real-time and allows the driller to make instantaneous changes to all drilling parameters. The simulator provides the rate of penetration, torque, standpipe pressure, and trajectory as output. This enables the user to have on-the-fly interference with the drilling process and allows him/her to modify any of the important drilling parameters. Thus, the user can determine the effect of such changes on the effectiveness of drilling, which can lead to effective drilling optimization. Certain intervals were investigated independently to give a more detailed analysis of the simulation outcome. Additional drilling data such as hook load and standpipe pressure were analyzed to determine and evaluate the drilling performance of a particular interval and to consider them in the optimization process. The resulting rate of penetration and well trajectory simulation results show an excellent match with field data. The simulation illustrates the continuous change between rotating and sliding mode as well as the accurate synchronous matching of the rate of penetration and trajectory. The results prove that the simulator is an excellent tool for students and professionals to simulate the drilling process prior to actual drilling of the next inclined well.

A Wellbore Pressure Calculation Method Considering Gas Suspension in Wellbore Shut-In Condition

2021 ◽  
Author(s):  
Zhi Zhang ◽  
Baojiang Sun ◽  
Zhiyuan Wang ◽  
Shaowei Pan ◽  
Wenqiang Lou ◽  
...  
Keyword(s):  
Yield Stress ◽  
Calculation Method ◽  
Optimization Design ◽  
Drilling Fluid ◽  
Drilling Fluids ◽  
Drilling Process ◽  
Gas Suspension ◽  
Wellhead Pressure ◽  
Suspension Concentration ◽  
Wellbore Pressure

Abstract In the oil industry, the drilling fluid is yield stress fluid. The gas invading the wellbore during the drilling process is distributed in the wellbore in the form of bubbles. When the buoyancy of the bubble is less than the resistance of the yield stress, the bubble will be suspended in the drilling fluid, which will lead to wellbore pressure inaccurately predicting and overflow. In this paper, the prediction model of gas limit suspension concentration under different yield stresses of drilling fluids is obtained by experiments, and the calculation method of wellbore pressure considering the influence of gas suspension under shut-in conditions is established. Based on the calculation of the basic data of a case well, the distribution of gas in different yield stress drilling fluids and the influence of gas suspension on the wellbore pressure are analyzed. The results show that with the increase of yield stress, the volume of suspended single bubbles increases, the gas suspension concentration increases, and the height at which the gas can rise is reduced. When the yield stress of drilling fluid is 2 Pa, the increment of wellhead pressure decreases by 37.1% compared with that without considering gas suspension, and when the yield stress of drilling fluid is 10Pa, the increment of wellhead pressure can decrease by 78.6%, which shows that when the yield stress of drilling fluid is different, the final stable wellhead pressure is quite different. This is of great significance for the optimization design of field overflow and kill parameters, and for the accurate calculation of wellbore pressure by considering the suspension effect of drilling fluid on the invasion gas through the shut in wellhead pressure.

A Robust Rate of Penetration Model for Carbonate Formation

2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Ahmad Al-AbdulJabbar ◽  
Salaheldin Elkatatny ◽  
Mohamed Mahmoud ◽  
Khaled Abdelgawad ◽  
Abdulaziz Al-Majed
Keyword(s):  
Compressive Strength ◽  
Drilling Fluid ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Drilling Process ◽  
Rate Of Penetration ◽  
New Model ◽  
Carbonate Formation ◽  
Drilling Parameters ◽  
Fluid Properties

During the drilling operations, optimizing the rate of penetration (ROP) is very crucial, because it can significantly reduce the overall cost of the drilling process. ROP is defined as the speed at which the drill bit breaks the rock to deepen the hole, and it is measured in units of feet per hour or meters per hour. ROP prediction is very challenging before drilling, because it depends on many parameters that should be optimized. Several models have been developed in the literature to predict ROP. Most of the developed models used drilling parameters such as weight on bit (WOB), pumping rate (Q), and string revolutions per minute (RPM). Few researchers considered the effect of mud properties on ROP by including a small number of actual field measurements. This paper introduces a new robust model to predict the ROP using both drilling parameters (WOB, Q, ROP, torque (T), standpipe pressure (SPP), uniaxial compressive strength (UCS), and mud properties (density and viscosity) using 7000 real-time data measurements. In addition, the relative importance of drilling fluid properties, rock strength, and drilling parameters to ROP is determined. The obtained results showed that the ROP is highly affected by WOB, RPM, T, and horsepower (HP), where the coefficient of determination (T2) was 0.71, 0.87, 0.70, and 0.92 for WOB, RPM, T, and HP, respectively. ROP also showed a strong function of mud fluid properties, where R2 was 0.70 and 0.70 for plastic viscosity (PV) and mud density, respectively. No clear relationship was observed between ROP and yield point (YP) for more than 500 field data points. The new model predicts the ROP with average absolute percentage error (AAPE) of 5% and correlation coefficient (R) of 0.93. In addition, the new model outperformed three existing ROP models. The novelty in this paper is the application of the clustering technique in which the formations are clustered based on their compressive strength range to predict the ROP. Clustering yielded accurate ROP prediction compared to the field ROP.

scholarly journals NETL Extreme Drilling Laboratory Studies High Pressure High Temperature Drilling Phenomena

2008 ◽  
Vol 130 (4) ◽  
Author(s):  
K. David Lyons ◽  
Simone Honeygan ◽  
Thomas Mroz
Keyword(s):  
Physical Simulation ◽  
Drilling Fluid ◽  
Fluid Pressure ◽  
Rock Properties ◽  
Drilling Fluids ◽  
Laboratory Studies ◽  
Drilling Parameters ◽  
High Pressure High Temperature ◽  
Fluid Properties ◽  
Weight On Bit

The U.S. Department of Energy’s National Energy Technology Laboratory (NETL) established the Extreme Drilling Laboratory to engineer effective and efficient drilling technologies viable at depths greater than 20,000 ft. This paper details the challenges of ultradeep drilling, documents reports of decreased drilling rates as a result of increasing fluid pressure and temperature, and describes NETL’s research and development activities. NETL is invested in laboratory-scale physical simulation. Its physical simulator will have capability of circulating drilling fluids at 30,000 psi and 480°F around a single drill cutter. This simulator is not yet operational; therefore, the results will be limited to the identification of leading hypotheses of drilling phenomena and NETL’s test plans to validate or refute such theories. Of particular interest to the Extreme Drilling Laboratory’s studies are the combinatorial effects of drilling fluid pressure, drilling fluid properties, rock properties, pore pressure, and drilling parameters, such as cutter rotational speed, weight on bit, and hydraulics associated with drilling fluid introduction to the rock-cutter interface. A detailed discussion of how each variable is controlled in a laboratory setting will be part of the conference paper and presentation.

Inline Drilling Fluid Property Measurement, Integration, and Modeling to Enhance Drilling Practice and Support Drilling Automation

2021 ◽  
Author(s):  
Sanjit Roy ◽  
Saiyid Z. Kamal ◽  
Richard Frazier ◽  
Ross Bruns ◽  
Yahia Ait Hamlat
Keyword(s):  
Real Time ◽  
Drilling Fluid ◽  
Measurement Data ◽  
Lessons Learned ◽  
Valuable Insight ◽  
Drilling Process ◽  
Time Data ◽  
Fluid Property ◽  
Real Time Data ◽  
Fluid Properties

Abstract Frequent, reliable, and repeatable measurements are key to the evolution of digitization of drilling information and drilling automation. While advances have been made in automating the drilling process and the use of sophisticated engineering models, machine learning techniques to optimize the process, and lack of real-time data on drilling fluid properties has long been recognized as a limiting factor. Drilling fluids play a significant function in ensuring quality well construction and completion, and in-time measurements of relevant fluid properties are key to automation and enhancing decision making that directly impacts well operations. This paper discusses the development and application of a suite of automated fluid measurement devices that collect key fluid properties used to monitor fluid performance and drive engineering analyses without human involvement. The deployed skid-mounted devices continually and reliably measure properties such as mud weight, apparent viscosity, rheology profiles, temperatures, and emulsion stability to provide valuable insight on the current state of the fluid. Real-time data is shared with relevant rig and office- based personnel to enable process monitoring and trigger operational changes. It feeds into real-time engineering analyses tools and models to monitor performance and provides instantaneous feedback on downhole fluid behavior and impact on drilling performance based on current drilling and drilling fluid property data. Equipment reliability has been documented and demonstrated on over 30 wells and more than 400 thousand ft of lateral sections in unconventional shale drilling in the US. We will share our experience with measurement, data quality and reliability. We will also share aspects of integrating various data components at disparate time intervals into real-time engineering analyses to show how real-time measurements improve the prediction of well and wellbore integrity in ongoing drilling operations. In addition, we will discuss lessons learned from our experience, further enhancements to broaden the scope, and the integration with operators, service companies and other original equipment manufacturer in the domain to support and enhance the digital drilling ecosystem.

Evaluation of Derived Controllable Variables for Predicting Rop Using Artificial Intelligence in Autonomous Downhole Rotary Drilling System

2021 ◽  
Author(s):  
Kingsley Williams Amadi ◽  
Ibiye Iyalla ◽  
Yang Liu ◽  
Mortadha Alsaba ◽  
Durdica Kuten
Keyword(s):  
Real Time ◽  
Specific Energy ◽  
Penetration Rate ◽  
Drilling Process ◽  
Stick Slip ◽  
Conservation Of Energy ◽  
Rate Of Penetration ◽  
Mechanical Specific Energy ◽  
Drilling Parameters ◽  
Drilling System

Abstract Fossil fuel energy dominate the world energy mix and plays a fundamental role in our economy and lifestyle. Drilling of wellbore is the only proven method to extract the hydrocarbon reserves, an operation which is both highly hazardous and capital intensive. To optimize the drilling operations, developing a high fidelity autonomous downhole drilling system that is self-optimizing using real-time drilling parameters and able to precisely predict the optimal rate of penetration is essential. Optimizing the input parameters; surface weight on bit (WOB), and rotary speed (RPM) which in turns improves drilling performance and reduces well delivery cost is not trivial due to the complexity of the non-linear bit-rock interactions and changing formation characteristics. However, application of derived variables shows potential to predict rate of penetration and determine the most influential parameters in a drilling process. In this study the use of derived controllable variables calculated from the drilling inputs parameters were evaluated for potential applicability in predicting penetration rate in autonomous downhole drilling system using the artificial neutral network and compared with predictions of actual input drilling parameters; (WOB, RPM). First, a detailed analysis of actual rock drilling data was performed and applied in understanding the relationship between these derived variables and penetration rate enabling the identification of patterns which predicts the occurrence of phenomena that affects the drilling process. Second, the physical law of conservation of energy using drilling mechanical specific energy (DMSE) defined as energy required to remove a unit volume of rock was applied to measure the efficiency of input energy in the drilling system, in combination with penetration rate per unit revolution and penetration rate per unit weight applied (feed thrust) are used to effective predict optimum penetration rate, enabling an adaptive strategize which optimize drilling rate whilst suppressing stick-slip. The derived controllable variable included mechanical specific energy, depth of cut and feed thrust are calculated from the real- time drilling parameters. Artificial Neutral Networks (ANNs) was used to predict ROP using both input drilling parameters (WOB, RPM) and derived controllable variables (MSE, FET) using same network functionality and model results compared. Results showed that derived controllable variable gave higher prediction accuracy when compared with the model performance assessment criteria commonly used in engineering analysis including the correlation coefficient (R2) and root mean square error (RMSE). The key contribution of this study when compared to the previous researches is that it introduced the concept of derived controllable variables with established relationship with both ROP and stick-slip which has an advantage of optimizing the drilling parameters by predicting optimal penetration rate at reduced stick-slip which is essential in achieving an autonomous drilling system. :

Evaluation of Ultrasonic Methods for In-Situ Real-Time Characterization of Drilling Mud

2005 ◽  
Author(s):  
Judith Ann Bamberger ◽  
Margaret S. Greenwood
Keyword(s):  
Physical Properties ◽  
Real Time ◽  
Speed Of Sound ◽  
Direct Contact ◽  
Drilling Fluid ◽  
Drilling Process ◽  
Drilling Mud ◽  
Well Control

A real time multi-functional ultrasonic sensor system is proposed to provide automated drilling fluid monitoring that can improve the capability and development of slimhole and microhole drilling. This type of reliable, accurate, and affordable drilling fluid monitoring will reduce the overall costs in exploration and production. It will also allow more effective drilling process automation while providing rig personnel a safer and more efficient work environment. Accurate and timely measurements of drilling fluid properties such as flow rate, density, viscosity, and solid loading are key components for characterizing rate of drill penetration, providing early warning of lost circulation, and for use in real-time well control. Continuous drilling fluid monitoring enhances drilling economics by reducing the risk of costly drilling downtime, increasing production performance, and improving well control. Investigations conducted to characterize physical properties of drilling mud indicate that ultrasound can be used to provide real-time, in-situ process monitoring and control. Three types of ultrasonic measurements were evaluated which include analysis of in wall, through wall and direct contact signals. In wall measurements provide acoustic impedance (the slurry density and speed of sound product). Through wall and direct contact measurements provide speed of sound and attenuation. This information is combined to determine physical properties such as slurry density, solids concentration and can be used to detect particle size changes and the presence of low levels of gas. The measurements showed that for the frequency range investigated in-wall measurements were obtained over the slurry density range from 1500 to 2200 kg/m3 (10 to 17 pounds solids per gallon of drilling fluid). Other measurements were obtained at densities in the 1500 to 1800 kg/m3 range. These promising measurement results show that ultrasound can be used for real-time in-situ characterization of the drilling process by monitoring drilling mud characteristics.

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