Enhancing production monitoring: A back allocation methodology to estimate well flow rates and assist well test scheduling

Production flow rates are crucial to make operational decisions,monitor,manage,and optimize oil and gas fields.Flow rates also have a financial importance to correctly allocate production to fiscal purposes required by regulatory agencies or to allocate production in fields owned by multiple operators.Despite its significance,usually only the total field production is measured in real time,which requires an alternative way to estimate wells'production.To address these challenges,this work presents a back allocation methodology that leverages real-time instrumentation,simulations,algorithms,and mathe-matical programming modeling to enhance well monitoring and assist in well test scheduling.The methodology comprises four modules:simulation,classification,error calculation,and optimization.These modules work together to characterize the flowline,wellbore,and reservoir,verify simulation outputs,minimize errors,and calculate flow rates while honoring the total platform flow rate.The well status generated through the classification module provides valuable information about the current condition of each well(i.e.if the well is deviating from the latest well test parameters),aiding in decision-making for well testing scheduling and prioritizing.The effectiveness of the methodology is demonstrated through its application to a representative offshore oil field with 14 producing wells and two years of daily production data.The results highlight the robustness of the methodology in properly classifying the wells and obtaining flow rates that honor the total platform flow rate.Furthermore,the methodology supports well test scheduling and provides reliable indicators for well conditions.By uti-lizing real-time data and advanced modeling techniques,this methodology enhances production monitoring and facilitates informed operational decision-making in the oil and gas industry.

Distributed optical fiber acoustic sensor for in situ monitoring of marine natural gas hydrates production for the first time in the Shenhu Area,China

The distributed acoustic sensor(DAS)uses a single optical cable as the sensing unit,which can capture the acoustic and vibration signals along the optical cable in real-time.So it is suitable for monitoring downhole production activities in the process of oil and gas development.The authors applied the DAS system in a gas production well in the South China Sea for in situ monitoring of the whole wellbore for the first time and obtained the distributed acoustic signals along the whole wellbore.These signals can clearly distinguish the vertical section,curve section,and horizontal production section.The collected acoustic signal with the frequency of approximately 50 Hz caused by the electric submersible pump exhibit a signal-to-noise ratio higher than 27 dB.By analyzing the acoustic signals in the production section,it can be located the layers with high gas production rates.Once an accurate physical model is built in the future,the gas production profile will be obtained.In addition,the DAS system can track the trajectory of downhole tools in the wellbore to guide the operation.Through the velocity analysis of the typical signals,the type of fluids in the wellbore can be distinguished.The successful application of the system provides a promising whole wellbore acoustic monitoring tool for the production of marine gas hydrate,with a good application prospect.

The safety parameters monitoring system for the coal mine based on CAN bus communication and intelligent data acquisition

In this paper,a monitoring and controlling system for the safety in production and environmental parameters of a small and medium-sized coal mine has been developed after analyzing the current domestic coal production and security conditions. The client computer can convert the analog signal about the safety in production and environmental parameters detected from the monitoring terminal into digital signal,and then,send the signal to the coal mine safety monitoring centre. This information can be analyzed,judged,and diagnosed by the monitoring-management-controlling software for helping the manager and technical workers to control the actual underground production and security situations. The system has many advantages including high reliability,better performance of real-time monitoring,faster data communicating and good practicability,and it can effectively prevent the occurrence of safety incidents in coal mines.

Cyber Secure Framework for Smart Containers Based on Novel Hybrid DTLS Protocol

The Internet of Things (IoTs) is apace growing, billions of IoT devicesare connected to the Internet which communicate and exchange data among eachother. Applications of IoT can be found in many fields of engineering and sciencessuch as healthcare, traffic, agriculture, oil and gas industries, and logistics. Inlogistics, the products which are to be transported may be sensitive and perishable, and require controlled environment. Most of the commercially availablelogistic containers are not integrated with IoT devices to provide controlled environment parameters inside the container and to transmit data to a remote server.This necessitates the need for designing and fabricating IoT based smart containers. Due to constrained nature of IoT devices, these are prone to different cybersecurity attacks such as Denial of Service (DoS), Man in Middle (MITM) andReplay. Therefore, designing efficient cyber security framework are required forsmart container. The Datagram Transport Layer Security (DTLS) Protocol hasemerged as the de facto standard for securing communication in IoT devices.However, it is unable to minimize cyber security attacks such as Denial of Serviceand Distributed Denial of Service (DDoS) during the handshake process. Themain contribution of this paper is to design a cyber secure framework by implementing novel hybrid DTLS protocol in smart container which can efficientlyminimize the effects of cyber attacks during handshake process. The performanceof our proposed framework is evaluated in terms of energy efficiency, handshaketime, throughput and packet delivery ratio. Moreover, the proposed framework istested in IoT based smart containers. The proposed framework decreases handshake time more than 9% and saves 11% of energy efficiency for transmissionin compare of the standard DTLS, while increases packet delivery ratio andthroughput by 83% and 87% respectively.