Autonomic wireless seismic sensor network with remote management

Abstract

The oil and gas are still promising energy sources and will continue for a few more decades. The exploration of new oil fields and maximizing the exploitation of these became the new challenge of this century. Optimize, reduce costs and reduce environmental impacts in prospecting, exploration and exploitation of oil and gas is a constant challenge. Shale that transformed the oil industry in the US, will spread beyond North America before the end of the decade. The unconventional reserves (shale gas) onshore in Brazil, already mapped, are considered significant, their resources may develop the gas market in the country, internalizing, in fact, the use of gas in the country. The ANP held the 12th round aimed at the exploitation of this resource type, at the end of 2013. As well as the large Brazilian onshore sedimentary basins, not yet prospected in its entirety, are considered as a great oil potential off the so-called "blue steak" (pre-salt). The advances that have occurred in the areas of microcontrollers (MCU) Microprocessors (MPU), remote sensing technologies, data transmission for Internet of Things (IoT) wireless sensor network (WSN), Micro-Electro-Mechanical Systems ( MEMS) and wireless communication protocols more efficient; in recent years have spurred the development of wireless seismic sensor networks (RSSFSis). The RSSFSis are composed of hundreds to thousands of seismic sensors, used primarily for monitoring and seismic exploration onshore hydrocarbon reservoirs based networks geophones and seismic accelerometers high sensitivity MEMS. The RSSFSis are usually deployed in normally uncontrolled environments, in large areas of several km2, making it difficult to maintain in place. Thus, energy saving, efficiency in data collection and fault tolerance of the components are the most important requirements considered. Currently, some bottlenecks RSSFSis have not yet been solved as continuous collection (no data loss) the large flow of data acquired by sensors and ensuring energy autonomy to the system for long periods of time, in order to maintain the acquisition units data the most possible light for its easy portability and handling in the field - the largest energy autonomy, the greater the number of batteries and weight acquisition unit. This difficulty leads to the need for research, development and innovation (RD&I) for new solutions in: hardware/software, collection of EH, embedded systems and Web applications for remote management and development of new forms (protocol) communication for efficient collection data based protocol transmission and timing requirements policies. So autonomic computing techniques are necessary. Thus it is proposed to this project: Autonomic Network Seismic Sensors Wireless Remote Management (RASSFWeb).One hopes at the end of phase I project, have a solution that enables prototyping larger scale, which can be developed in the final product as a scalable and autoconfigurável RASSFWeb. So in this way, providing an innovative national solution (autonomic network with EH) and lower cost compared to foreign traditional solutions and closed technology. The RASSFWeb will be used primarily to: permanent micro seismic monitoring of conventional and unconventional reservoirs of hydrocarbons, time-lapse 4D seismic onshore, Passive Seismic exploration and onshore hydrocarbon using the methods of 2D and 3D seismic. The RASSFWeb project is currently under development, beginning in January 2015, aided design, early stage and therefore the CNPq human resources training program in Strategic Areas (RHAE). The benefit achieved by RHAE Faixa-A for this project are two scholarships for top-level experts in the field of embedded systems (hardware/firmware). (AU)