Currently the super-viscous oil deposits are under active development in the Republic of Tatarstan. The general method of production is Steam-Assisted Gravity Drainage (SAGD). The problem of creation the complex of methods to monitor and control the reservoir processes caused by steam injection is of a great importance for increasing the development efficiency. Traditional control methods of shallow deposits development are normally based on seismic survey and whether insufficiently adatped for shallow deposits of super-viscous oil or very expensive. Thus, the special modifications of geophysical methods are required. The paper discusses general approaches used for creation of complex of methods for steam chamber monitoring the oil production from the shallow deposits of super-viscous oil by SAGD. The methods developed include seismic and geoelectric survey. In context of integrated monitoring technique creation the set of special core survey was conducted to define the possibility of detection of the steam chamber distribution by seismic methods. The distinguishing feature of the monitoring technology developed is the use of downhole monitoring tools to receive the seismic signal and to perform the geoelectrical field establishing. The article contains the description of the seismic data obtained processing methods and the results of the seismic data interpretation. The study was made with the financial support of Ministry of Education and Science of the Russian Federation (project № №02.G25.31.0170)

Summary This paper presents the efficiency of using artificial neural networks for solving problems of processing and interpreting geophysical data obtained by scanning magnetic introscopy. Neural networks of various architectures have been implemented to solve the problems of processing primary material, searching for well structure objects,identifying casing defects. The analysis of the capabilities of neural networks in comparison with mathematical algorithms is carried out. To test machine learning algorithms and mathematical algorithms for processing, visualizing and storing the results, a software shell was created in which all tasks are solved using a set of tools. It was found that the use of artificial neural networks can significantly speed up the process of data processing and interpretation, as well as improve the quality of the results in comparison with individual mathematical algorithms. Nevertheless, the use of mathematical algorithms in solving some problems gives consistently better results. In particular, the problematic aspects were identified at the stage of interpretation when identifying defects. This is due to the presence of conventions in the isolation of defects by the operator at the stage of preparing data for training neural networks, which is a subjective factor and requires a deeper study.

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This work describes the features and design of the acoustically semitransparent cover of a borehole ultrasonic imager with high resolution. This scanner is designed to investigate the fine structure of the well surface by ultrasonic sounding method at a frequency of 800 kHz. The ultrasonic transducer is rotating around a central axis. However, in the design of the device fixed semitransparent protective cover is provided for prevent damage of mechanical parts. Nevertheless, during reflected signals recording from the wall of well the undesirable noise reflections appear from protective cover. These noises interfere with the algorithm of detecting the main signal. The logging tool electronics is based on a single FPGA chip, its logic cells capacity allows determining the maximum reflection amplitude and its location, as well as recording the signal time window to the SD-card (with 32GB storage space). This windows are processed at the personal computer after logging. Such approach allows analyzing waveforms and noises. After a multiple laboratory and well experiments this logging tool was allow improving the design of the acoustically semitransparent protective cover for maximum attenuation of the reflection noise. In addition, the forms of the recorded acoustic signals and the design of the protective cover are given.