Well Collision Detector

The ability to predict the useful life remaining for a drill bit or estimate the dull grading in real time while drilling with high accuracy is valuable for planning and real-time decisions within well construction. Domain experts and software engineers have developed a workflow that utilizes the company's global offset well database and bit knowledge to feed an intelligent decision-making system that can enhance the drilling process and prevent excessive bit damage by calculating the efficiency of the bit and predicting if the dull grading at the end of the run will be beyond a certain limit. The workflow was implemented on an existing software platform and validated on more than 100 wells, with insights gained from more than 44,000 offset wells’ detailed depth data from the company's global database. In real time, it is shown to enhance drilling efficiency and help make decisions to keep drilling or pull the bit out of the hole. The approach involves planning and execution stages. During the planning stage, experts analyzing offset data establish drill bit performance benchmarks. This step is powered by an automated offset well selection algorithm based on job similarity. These benchmarks integrate comprehensive metrics such as average rate of penetration (ROP), drilled footage, and bit damage conditions, as well as drilling mechanics and bit performance indices calculated along drilling depths of offset wells. In the execution stage, real-time data is used to compute drill bit performance indices, which are then compared against the established benchmarks. Accumulative bit damage is assessed through proprietary computations in the application. Inefficient drilling, hard stringers, and interbeds are detected in real time using machine learning methods. Advice is automatically generated to apply the best drilling practices based on detected drilling challenges. Alerts are generated based on predicted bit damage. The advice and alerts are reviewed by remote operation experts who provide actionable recommendations to the drillers. Millions of bit performance summaries and tens of thousands of bit run data with detailed surface or downhole measurements have been utilized as the foundation of the workflow. A process, enriched with domain expertise, has been developed to efficiently construct offset benchmarks. The bit damage model has been validated across multiple fields, achieving an accuracy of more than 85%. Field tests confirm the workflow's effectiveness in providing real-time, relevant advisories to drillers, with remote operation experts in the loop. This approach has been proven to better separate bit performance variations due to bit damage rather than formation changes, which has been a challenge for many prior bit performance and damage monitoring methods. This paper describes how these computations can be used to determine the performance of the bit in real time. Included are overviews of the data used. Results and validation of all workflows will also be discussed. The workflow is the industry's first to utilize a large-scale global drill bit database for real-time bit performance benchmarking and prediction. It combines data-driven insights with domain expert inputs to help make decisions.

Collision detection and inspection of industrial robots have become essential functions in modern industrial automation. Sensor-based detection methods are commonly employed in research to achieve collision detection, including high-precision force sensors, ultrasonic ranging sensors, electronic skins, and others. While collision detection using force sensors or electronic skin sensors offers very high accuracy, the inclusion of these sensors increases the overall cost. This article proposes a solution using dynamic modeling for collision detection. First, the theoretical torque generated by each axis of the industrial robot under different pose conditions is analyzed in real time. Then, the actual torque is calculated by sampling the motor current of each axis. By setting error margins and collision detection thresholds, collision detection can be achieved in a cost-effective manner without the need for additional sensors. Experiments were conducted to evaluate this dynamic modeling approach to collision detection. The findings indicated that the approach is efficacious and capable of identifying the impacts of diverse collision objects. However, compared to sensor-based detection methods, collision detection using dynamic modeling has the disadvantage of lower accuracy. Future research will concentrate on enhancing the calculation accuracy of the theoretical torque to enhance the sensitivity of collision detection.

Raudhatain Field North Kuwait is produced with approximately 500 oil wells of which over 200 use Electrical Submersible Pumps (ESP). The ESP is used as a production mechanism to supplement the natural reservoir drive of the wells. Downhole monitoring of the ESP system is one of the most important aspects in maximizing ESP performance with the final objective of increasing in ESP run life and maximize oil production. An old ESP Monitoring system was introduced few years back, however the application and utilization did not fully support the concept of ESP Real Time Monitoring. The new ESP Real Time Monitoring system has been recently introduced to complement the old system. This new system has more significant improvement over the old system. A SCADA system has been utilized to transmit ESP data from well site to the server in the office that allows the engineers to retrieve real time data, monitor the parameters and perform analysis and take necessary actions in the well. Advances in measurement technology have made ever increasing amounts of real time information available for monitoring both pump and well performance. Parameters such multiple downhole pressure readings, temperature and vibration, well head pressure readings as well as the traditional operating voltages and amperages are not only available, but available in real-time at the engineers desk top. Having all of this data on our desk tops has created an environment that allows the engineer to change for a reactive monitoring approach as problems are identified, to a proactive tool, catching potential issues before they become problematic to the ESP performance. The ability of the new ESP Real Time Monitoring Tool to perform data trending of an ESP for any date or time frame, evaluating either some or all of the critical parameters, has allowed the engineers in Raudhatain field to analyze ESP performance more accurately through trend analysis. This allows an engineer to review well performance in a matter of minutes compared to the hours used in the past. This has helped the engineers in making faster more accurate decisions. This paper will address several examples where ESP real-time monitoring lead to an incremental of 3,000 BOPD production North Kuwait Raudhatain field will continue the utilization of this ESP Real Time Monitoring system and seek further improvement. This paper will describe the system, share our experiences and show how the system helps in ESP optimization and, thus maximize production.

It is important to measure and analyze offshore platform motion data for the safety of offshore platforms that are installed in an extreme environmental conditions. Especially, in the Gulf of Mexico, because of the hurricane and loop current that has been strengthened due to changes in the ocean environment, a monitoring system is necessary to measure the offshore platform motion data in real time, as well as simultaneously analyze it for safe operation and accident prevention. In order to develop such a monitoring system, it is extremely critical to obtain accurate data. However, since data measured in real time is not suitable for analysis due to quality problems, the data must be processed. The problem is that the processed data differs depending on the processing methods being employed, and results in entirely different analysis results. Incorrect results can mislead the current state of the offshore platform causing missed maintenance periods or, in the worst case, major accidents. Therefore, verifying both the adequacy of the methods used to process the data and the accuracy of the results is most vital. In this paper, improving reliability of the monitoring system that can measure offshore platform motion data and analyze data in real time, the validity of the method used in measurement data processing and the accuracy of the processed data were verified.

Real time solutions: an innovative approach to making business-time critical driven decisions. It is designed to monitor, support, and optimize operations in real time and remotely to mitigate cost and risk at work sites. The workflows allowed real time monitoring and intervention of the drilling operating parameters from the office which resulted in greater operating efficiency and thus greater financial saving. This technology was instrumental to the Angsi development team's success in drilling Malaysia's longest development well to-date, Angsi-A028ST1 at a total depth of 6,339 meters.Real time well construction workflows begin when real time data on the rig site are gathered and transmitted to PETRONAS Carigali Sdn.Bhd, PCSB office via VSAT link. Data can be accessed via a web-based interface for 24 hours coverage anytime anywhere. The real time data are integrated into a geological and geophysical project database and fed into a 3D visualization tool which amalgamates the planned and current well trajectories within the geological earth model incorporating neighbouring wells with operations data. The simultaneous display of "knowledge-management-cubes" from daily drilling operational reporting software enables the team to review contingency plans and be pre-emptive by the captured lesson learnt.This technology creates multidisciplinary collaborations through the ether space, reducing communication gaps and greatly improving the decision making process. Examples: reducing the number of check trips, shortening the planned TD by comparing the real time data against correlated model, and helping in handling operational problems. The team has greatly benefited from RTO - technologies, people and processes - with a total cost saving of more than USD 1 million.This paper presents the real time system setup, architecture and scope of work in enabling 2D and 3D well visualization and integration. The value-added and the relative cost savings, observations and feedback are also presented

A new numerical procedure for the study of finite temperature quantum dynamics is developed. The method is based on the observation that the real and imaginary time dynamical data contain complementary types of information. Maximum entropy methods, based on a combination of real and imaginary time input data, are used to calculate the spectral densities associated with real time correlation functions. Model studies demonstrate that the inclusion of even modest amounts of short-time real time data significantly improves the quality of the resulting spectral densities over that achievable using either real time data or imaginary time data separately.

Securing the verticality of foundations is a crucial factor for ensuring safety in offshore construction. The repeated intrusion-pulling method is generally used to ensure verticality in suction bucket foundation construction processes. However, it relies heavily on the experience and skills of field workers and is relatively time-consuming. To address this problem, we propose an automatic verticality securing system for large circular steel pipes based on a verticality monitoring system. This system adjusts cables at locations where verticality correction is required without changing the existing suction pile–penetration–construction process. It includes a monitoring component that provides real-time data on pipe alignment and an automatic lifting cable control system that maintains perpendicularity using data acquired from the monitoring system. The monitoring system comprises a sensor, an embedded controller, and a display program that displays the vertical information of circular steel pipes. The automatic lifting cable control system includes a controller with an algorithm for adjusting the length of the actuator. We showed that the system operates satisfactorily and secures the verticality of less than 0.2° in the suction bucket-based model experiment. Furthermore, the testbed experimental results show that our monitoring system can efficiently measure verticality information in real time.

Water quality monitoring (WQM) system is widely being explored as it is needed to prevent the problem of water contamination worldwide. Nowadays, there are various studies on WQM system that are being integrated with Internet of Things (IoT) concept for Wireless Sensor Network (WSN) technology implementation to get real time data measurement. Traditional ways of collecting the data are more time consuming and they lack real time changes in the quality of water. This paper presents the development and implementation of Water Quality Assessment and Monitoring (WQAM) system. The system development used WiFi enabled microcontroller to connect with the IoT environment and store the data in the IoT cloud server. The microcontroller used is Arduino UNO that interacts with three types of sensor probes which are pH, turbidity and temperature probe. All the data measurements is transferred using a WiFi module which is ESP8266. The IoT cloud used to utilize the data frame is ThingSpeak. This system was implemented on Bandar Perda Lake and Derhaka River in Pulau Pinang with two systems implemented at each location. The sensors were placed on the water surface for more accurate measurements. This system continuously measures the readings of pH, turbidity dan temperature on the lake/river for every 1 hour. Twenty readings were taken for every 1 hour within the first 20 minutes with 1 minute interval and the readings were stored in the IoT cloud server. The readings are accessible via ThingSpeak GUI. In conclusion, this system would benefit the authorities to take advantage of using the WQAM system with the aid of the IoT that is less time consuming, less cost and more reliable in real time data reading.

Abstract— NavMorpho – Smart Vehicle Safety and Monitoring System is a cutting-edge, real-time intelligent safety solution designed to enhance road safety and reduce accident-related fatalities. The system aims to provide automatic crash detection, live vehicle tracking, obstacle monitoring, and instant emergency alert transmission.This innovative solution integrates IoT technology with advanced sensors to monitor vehicle movement and detect accidents in real time. The system provides immediate emergency communication by automatically sending live GPS location data to registered emergency contacts when a crash is detected.The ESP32-based system consists of multiple hardware components including an MPU6050 accelerometer and gyroscope for crash detection, ultrasonic and IR sensors for obstacle monitoring, and a GPS module for real-time location tracking. The system connects to the internet using WiFi, enabling real-time data transmission to a cloud-based backend developed using Node.js and MongoDB.The cloud platform processes vehicle data, stores crash history, and updates a live monitoring dashboard. Upon detecting a crash, the system automatically triggers WhatsApp alerts containing the vehicle’s live location. A manual emergency button is also integrated to allow users to send instant alerts when needed.NavMorpho provides a smart, scalable, and life-saving solution for modern vehicles by combining IoT hardware, cloud computing, and real-time communication technologies. The system has strong potential to transform vehicle safety systems into intelligent, automated emergency response platforms. Keywords: ESP32, MPU6050, NEO-6M GPS Module, Ultrasonic Sensor

Environmental factors have a direct impact on the development of agriculture, so it is particularly important to detect the environment of the agroecological cycle index system. Although there are some plans for environmental monitoring, most of them are environmental monitoring for a larger concept, but this study is specific to the actual object. This article takes farmland as the research object and comprehensively uses embedded technology, information monitoring technology, and network technology based on the analysis of the research status and system application of the farmland environmental monitoring system. This article studies and designs a real-time online remote monitoring system for farmland ecological environment based on embedded architecture and GPRS technology. By using sensors to obtain farmland information, it is displayed on the monitoring center and mobile client, and data information is obtained in real time. It manages and protects the farmland environment in advance. This article measures and analyzes the data from the final experiment. The experimental results show that the monitoring system can accurately collect farmland data in real time. And through the embedded server and the Internet, the data can be remotely transmitted in real time and displayed on the monitoring center and mobile client software. The results showed that PM2.5 was 30 μg/m3 at 20:00. The experimental data have the characteristics of real time and stability, which can meet the requirements of real-time network remote monitoring and transmission of data.

Tacoma Narrows Constructors (TNC) is building a new suspension bridge in Tacoma, close to Seattle, Washington State, USA. The new bridge will be built just south of the existing bridge mounted on two caissons, referred to as East Caisson (Tacoma side) and West Caisson (Gig Harbor side). Each caisson is about 80’ wide and 130’ long in plan. The caissons are moored in place in high currents in the Narrows by two sets of mooring lines on each of them — lower set and upper set. The target positions of the new caissons are very close to the existing pier. Therefore the motions of the caisson are very critical for the success of the project and the final touchdown position of the caisson is also of main concern. The mooring monitoring and advisory system ZenMAS has the capability of monitoring the performance of the caisson in currents by acquiring real time data from instruments. Real time line tensions and GPS data are read. The instantaneous tension in each of the mooring lines is measured, recorded and reported. Using the real time GPS data, the program reports the translations and rotations of the caissons. There are warnings when any of these are exceeded beyond allowable limits. ZenMAS also has the capability to function as a simulation tool. Future what-if scenarios can be studied using this software and any necessary corrective measures taken. The analysis capabilities of ZenMAS include static and dynamic analysis using the Motion Simulator program MOTSIM [2]. Graphical representation of instantaneous caisson position and summary and detailed output and results are available from the program. A discussion on how this system was designed, typical inputs, outputs, and comparison to actual measured values is made in this paper.

Taking a byte out of big data

Automatic optical inspection (AOI) of micro drill bit becomes more and more important with the rapid expanding of printed circuit board (PCB) manufacturing industry. Distinguished from most traditional manual inspection approach, AOI is time-saving, objective and non contact. In this work, a pattern classification method is proposed for the AOI of micro drill bit in PCB manufacturing, in which three features of drill bit blade are extracted for classification. In order to be independent on the clamp that can guarantee the exact position of drill bit blade for photography, and reduce the cost of the AOI system, an image registration method is used to align the drill bit blade, which can also make the feature extraction much easier. The evaluation result indicates that the approach works well for the AOI of micro drill bit. It is real time, more detailed result providing and low requirement on photographic device.

We monitor the seismic signal emitted from a rotating drill bit in real time with an array of seismic sensors at the seafloor. Drill-bit seismic signals provide information to locate the drill-bit position itself and to image geological objects ahead and around the drill bit for geosteering purposes during drilling operations. The data can be obtained in real time without the need to stop drilling for logging and without any additional downhole instrumentation in the bottom hole assembly. Drill-bit positioning accuracy is independent of measured depth and with meter level lateral precision. This is significantly better than conventional downhole gyro-based methods, especially for long horizontal wells. With sources along the drilled well path approaching a target reservoir we obtain a 3D reverse VSP (RVSP) image around the well for prediction ahead of the drill bit. This paper presents a case study from the Grane reservoir in the North Sea, where we utilize a permanent reservoir monitoring (PRM) array for listening to signals emitted from drilling with a PDC bit. We present imaging results from a highly deviated well and compare them to 3D seismic. The field example shows the ability to look ahead several hundreds of meters below the drilled well trajectory.

In present day technology there is an immense need of developing suitable data communication interfaces for real time embedded systems.Field Programmable Gate Array (FPGA) offers various resources, which can be programmed for building up an efficient embedded system.In recent years the SOC (System on Chip) design eg, in media processing [1] is becoming more and more important in real time embedded applications as SOCs require low power, low area but are still capable of implementing various complex functionalities.In order to achieve SOC architecture, which can run a real time application, we need to develop high-speed data interfaces of the system with the external world through its various I/O ports.The DMA controller, which sends the data from I/O to memory and vice-versa without intervention of the processor, thus plays a vital role in these systems in order to achieve faster I/O data transfer.This paper proposes a technique to implement a DMA controller core on Spartan 3A FPGA hardware, which serves as an essential component for developing a real time data acquisition and processing system.