Thermal Wellbore Failure Detection Case Studies: A High Temperature Multi-Finger Caliper Surveillance Approach

Cooling of thermal wellbores such as steam assisted gravity drainage (SAGD) and cyclic steam stimulation (CSS) wells, is a common prerequistite to allow deployment of logging instruments due to the temperature limitation of imaging instruments’ electronics (<150°C). This paper presents a memory caliper technology housed in a thermoshield that can perform at up to 220°C, with the acquired data used to evaluate the integrity of tubulars and completion items (metal loss, deposition, deformation, and gap/hole damage), negating the need for cooling before deployment. Two cases are presented. One is a SAGD well with liner screens across the lateral section. The memory multi-finger caliper was deployed using coiled tubing and the data were successfully obtained across the lateral section with a maximum recorded temperature of 169°C. The second example is a vertical well in a steam flood field. Because of the uncertainty over the downhole temperature at the time of the well intervention, a temperature sensor was deployed in surface read-out mode above the caliper. This ensured the 220° temperature limit of the caliper would not be breached, and a maximum temperature of 208°C was recorded. The data confirm the feasibility of acquiring high accuracy/high resolution data from thermal wellbores without having to resort to manipulative cooling techniques to attain a temperature below 150°C. Enlargement of a limited entry perforation (LEP) was observed in the horizontal well and buckling was clearly detected in the vertical well. The broad measurement range of the caliper – 1.85" – 7.2" – enabled both the tubing and liner to be logged in a single well intervention, which facilitated a swift resumption of of steam injection activities. Ultimately, the high temperature MFC's ability to minimize deliberate cooling the thermal wellsbore before deployment, has time and cost saving implications throughout the life cycle of the well. Much of the existing literature examining downhole data acquistion in thermal wells, for the diagnosis of wellbore integrity issues, has relied on technologies that are unable to withstand temperatures much greater than 150°C. The ability to execute well interventions for data acquistion at higher temperatures offers the potential for empirical studies that compare the status and integrity of the wellbore completion in thermal and cooled conditions.

Potential Energy Production from Biogas Economically and Environmental Profitable. Case Study: Establishing a Batch Digester in “Fogi” Farm

Recently the use of biomass for biogas production is very limited in Albania. According to data acquistion from the study, the highest share in the entire structure of urban solid waste is that of organic waste 41-61.2%. A large part of these waste are bio digestible and can used for production or utilized as potential substrate in anaerobic digestion to produce biogas, a renewable source of energy and environment friendly too. Live stocks waste and especially cow manure farms are concerned in this study because there are a high number 11813 of them are spread all over Albania. In addition, the amount of cow manure exceeds 37,693.92 ton/year. In this case study is presented a cow farm located near Tirana, capital city of Albania with 200 cow heads which in the future will become 700 cow heads. The total amount of cow manure produced in this farm is 1825 ton/year, a considerable quantity of manure available for biogas production. This paper presents the type of digester, calculation of the biogas production yield, the optained energy, the pay back period of the initial investment and the net present value of this farm batcher digestor.

Parkinson Disease Detection Based on Voice and EMG Pattern Classification Method for Indonesian Case Study

Parkinson disease (PD) detection using pattern recognition method has been presented in literatures. This paper present multi-class PD detection utilizing voice and electromyography (EMG) features of Indonesian subjects. The multi-class classification consists of healthy control, possible stage, probable stage and definite stage. These stages are based on Hughes scale used in Indonesia for PD. Voice signals were recorded from 15 people with Parkinson (PWP) and 8 healthy control subjects. Voice and EMG data acquistion were conducted in dr Kariadi General Hospital Semarang, Central Java, Indonesia. Twenty two features are used for voice signal feature extraction and twelve features are emploed for EMG signal. Artificial Neural Network is used as classification method. The results of voice classification show that accuracy for testing step of 94.4%. For EMG classification, the accuracy of testing of 71%.

A Framework for Autonomous Wind Farms: Wind Direction Consensus

Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. In an autonomous wind farm, enabling cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving an autonomous wind farm is to develop algorithms that provide necessary information to ensure reliable, robust, and efficient operation of wind turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquistion (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. This article presents a framework for implementing an autonomous wind farm that incorporates information from local sensors in real time to better align turbines in a wind farm. Oftentimes, measurements made at an individual turbine are noisy and unreliable. By incorporating measurements from multiple nearby turbines, a more robust estimate of the wind direction can be obtained at an individual turbine. Results indicate that this estimate of the wind direction can be used to improve the turbine's knowledge of the wind direction and could decrease dynamic yaw misalignment, decrease the amount of time a turbine spends yawing due to a more robust input to the yaw controller, and increase resiliency to faulty wind-vane measurements.

Design and Implementation of a distributed software architecture for data acquistion systems

This paper will demonstrate the advantages of using a distributed software design for collecting environmental data. The design part will focus on achieving modularity through message queuing technologies. The essential components of the software implementation will be detailed. Finally, the testing results will be disclosed.