The techniques used to process open-and cased-hole image logging and other oriented tools that are run in offshore exploration and development wells require highly accurate navigation logs. Navigation packages usually consist of triaxial accelerometers and magnetometers that require calibration of the offset (bias), gain, and tool axis alignment for each sensor. Despite pre-or postacquisition surface calibrations, the downhole environment will alter calibrations of offset and gain as a result of many factors, such as temperature and electrical noise. These factors are impractical to characterize or predict, and it is impossible to completely isolate the navigation package from these factors. Experience shows that the offsets and gains of the sensors may change appreciably over time scales much shorter than the total logging time.This paper provides four detailed examples of possible navigation logs with various problems to develop a methodology for evaluating their quality and proposing corrective action. The goals of this study are to determine which navigation sensors to adjust or which sensors are not responding to the appropriate Earth field and need reconstruction. The paper proposes several quality measures for identifying, from the navigation log, drift in sensor response, including measured total field variations and correlations of tool deviation to tool rotation.When the methods described in this paper are used to align images with respect to a geographical reference (in cases where the navigation was affected by sensor failure or external factors, e.g., permanently magnetized formation layers, that alter the sensor calibrations), they significantly enhance the navigation quality. For example, image logs that originally wobbled erratically in ferrous formations can be oriented to the north allowing dipping-bed orientation to be measured. In addition, magnetometer reconstruction and accelerometer correction can easily manage oriented navigation in metal casing. In general, the algorithms developed in this study assume that a rough surface calibration is available to obtain an initial solution, but time is no longer required for meticulous wellsite surface calibration.

Leaks in wellbore tubulars emit acoustic waves in the borehole, which can be captured by a hydrophone array. Processing the array data yields location and energy level of the wellbore leaks; however, the hydrophones may also capture other coherent noise propagating as guided waves along the borehole, such as road noise caused by the displacement of logging equipment on the wellbore surface, by vibration from surface production facilities, and by distant loud leaks. Such coherent acoustic noise largely interferes with the estimation of a target leak's characteristics. Conventionally, to record higher-quality data, additional recordings may be required to station the tool at selected locations; however, this standard approach prolongs the acquisition time and constrains the vertical resolution. This paper describes an advanced approach to estimate and subsequently remove the guided-wave noise from the array hydrophone data to improve the accuracy of leak source locations. Furthermore, estimating the propagation direction and amplitude of leak-induced guided waves aids logging operations to efficiently locate a leak source. We propose an array data processing approach to separate the guided-wave noise from the direct arriving leak signal. The upward and downward propagating guided waves are identified using a least-square wave separation method. An alternative time-domain stacking method is also proposed for real-time fast computation. The slowness of the guided wave is optimized within a range and then used to estimate and remove the guided waves. Furthermore, characteristics of the estimated guided-wave noise can be extracted, such as the propagation direction, amplitude, and slowness. These parameters plotted in discrete depth locations provide additional information on the well condition. Synthetic and field data results show that the proposed method significantly improves the accuracy of the 2D flow map by removing the erroneous map artifacts due to guided waves. The low-frequency energy due to guided waves is also removed from the frequency spectrum log. The amplitude difference between the upward and downward propagating waves indicates the source direction of the leakage-induced waves. Hence, monitoring the guided wave amplitude and direction in real time provides an efficient way to quickly locate a leak source and reduce operation time. Conventional noise logging data are commonly contaminated by guided-wave noise. Single hydrophone tools cannot separate out these guided waves. The proposed approach, using a hydrophone array for separating guided-wave noise from direct arriving leak signals, provides a high-quality estimation of the energy and location of leaks in wellbore tubulars.

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To ensure the continuation of safe and reliable well operations diagnosing well health issues becomes increasingly necessary. Having access to the right technology can provide greater confidence in diagnostics data; enabling more effective well management and risk mitigation. As a prudent operator, bp is proactive and rigorous in monitoring the health of its well stock and is continuously introducing new technology and methods to increase the effectiveness of its surveillance capabilities. Traditionally, a combination of passive acoustics and temperature has been deployed in such investigations, but historically this has yielded limited success in offshore wells due to the combination of complex overprints. Whilst it is still acknowledged that passive acoustic logging does have limitations, chiefly due to their inability to characterize sporadic signals, next generation passive acoustics technology equipped with spectral sensor arrays have significantly enhanced abilities to measure subtle acoustic signals. This paper details an approach utilized offshore Azerbaijan for such diagnostics work, using these latest passive acoustic technologies, teamed with conventional temperature and distributed fibre optics. As part of routine and ongoing data gathering, different tools were tested across a multi-well campaign in a variety of environments and different well states; static, active annular bleed and whilst applying pressure to annuli. Previous logging programs have deployed passive acoustic tools to confirm pre-existing notions of well issues. The logging programs described in this paper used higher sample densities and longer station intervals to enable a detailed and objective view of well health. There were thousands of stations acquired in more than 10 runs across production, water and gas injector wells. The acquired dataset generated a vast number of data points across different fluid types, completions and well conditions which allowed a more robust assessment of tool repeatability, sensitivity and spectral response. Highly sensitive hydrophones in modern spectral passive acoustic logging tools along with temperature and fibre measurements integrated with other information helped our understanding of the dynamics behind the casing, allowing us to make better informed decisions about wells operations. As the datasets grew in size, quick-look processing methodology was developed to identify and characterize acoustic anomalies. The paper will demonstrate how the techniques developed have generated more confidence in passive acoustic technology. It will show how both acquisition procedures and data processing techniques were optimized to ensure the best quality answer products were delivered.

Borehole acoustic tools that use broadband source excitation functions can optimally excite multiple frequencies at nearly the same time, yielding a wide range of different formation acoustic response properties in the received signal. However, the analysis of received broadband signals is not straightforward in the time-domain because standard time semblance algorithms suffer from interference when received acoustic modes with different slownesses and frequency content arrive at a similar time. Another method, frequency semblance, is computationally expensive and is sensitive to noise and to other effects. We propose using specially designed phase filters that can move (delay) individual frequency contributions differently in time without changing the spectral amplitudes of the received signal, thus enabling existing time semblance methods to perform optimally at many frequencies by separating the received spectra in time.