Implementation of the Advanced Passive Acoustics Hardware and Software Complex for Well Integrity Diagnostics

To ensure operational stability of the unified gas supply system depending on the seasonal gas demand fluctuations, the underground gas storage facilities are effectively used. Well integrity diagnostics using the advanced logging techniques facilitate timely identification of potential problems (pinpointing cross-flows behind casing, detecting leaks in production casing and other well construction components, locating sustained annulus pressure sources etc.), and, thereby extension of the safe operation life of functioning of the underground gas storage facilities. The results of the complex of field and geophysical studies in several underground gas storage wells are given in this article. Different types of the underground gas storages are reviewed: the ones located in an aquifer, salt dome, and mature field. The diagnostics was carried out based on the complex of downhole logging including a passive acoustic tool. The passive acoustics hardware and software technology can capture and interpret acoustic signals generated by the wellbore or reservoir flows. To recognise and interpret the captured signals, the temporal coherence algorithms, data wavelet filtration, and neural networks are used. The use of this technology allows to significantly improve the safety of well operation. The information obtained is used both in the preparation of industrial safety expert reports and for the development of effective programs for major repairs of the underground gas storage wells located in the depleted gas and water fields, as well as in the salt caverns. Hardware and software technology of passive acoustics is being used in almost all the major oil and gas provinces in the world, receiving recognition from the largest domestic and foreign companies, however, this is the first time that underground gas storage facilities are used to check the technical condition of the wells.

Экспериментально обучаемый метод фильтрации шумов рассеяния в сигналах оптической когерентной томографии-=SUP=-*-=/SUP=-

A method for wavelet filtration procedure training for optical coherence tomography (OCT) images using the experimental measurements of test objects that were constructed by means of water solutions of monodisperse nanoparticles and several microscopic inclusions has been described in the present paper. The choice of test-object parameters (concentration of water solution, size of nanoparticles, and shape, dimensions, and mutual position of inclusions) has allowed the modeling of various working conditions of OCT and setting different criteria for estimation of filtration efficiency. In the present work, the optimal filter for the considered example of a test object has been selected among the combinations of various basic functions of five wavelet families, soft and hard threshold filtering methods, four decomposition levels, and threshold values in a range of 0.05–3.05. The mutual position of the micro-inclusions has been used as a criterion for evaluating the filtration efficiency. As a result, it has been shown that the determined wavelet filter leads to effective suppression of the scattering noise in OCT images and preserve information about the structure of the object under study.

EMI Soft-Sensing and Filter Based on Wavelet Applied in Underground Monitoring System

In order to enhance Electromagnetic Compatibility (EMC) of monitoring system, the EMI distribution should be obtained. But the measurement could not be accomplished perfectly because of underground condition. A novel EMI soft-sensing method was proposed to measure the electromagnetic interference(EMI) indirectly. The wavelet time-frequency analysis was introduced to monitoring system and the EMI source could be ascertained. The startup time, duration and waveform could be detected based on the running records of underground electric equipments. The electrical fast transient/burst (EFT/B), the most outstanding interference, was studied to verify the validity of wavelet analysis. EMI filter was improved in accordance of the EMI gotten from wavelet analysis. Power port immunity was developed obviously. Therefore the EFT/B of data port was restrained markedly with wavelet filtration. Coordinative effect of EMI power and wavelet filter resulted in reduction of false alarms. Results indicate that wavelet analysis and the improved EMI filter have enhanced the EMC of monitoring substations and sensors obviously. It is concluded the wavelet analysis is of guiding significance to measure underground EMI distribution and EMC of the underground monitoring system.