Compressing seismic migration parameters by B-spline surface fitting
Seismic migration needs many kinds of parameters. The parameters are scattered data and have a large amount of data points. In order to improve the numerical efficiency of seismic migration, the enormous parameter files need be compressed. The published methods for compressing scattered data have a few shortcomings, for example, some are not suitable for enormous data, some are time-consuming, and some can't provide high enough numerical precision. I propose a rapid algorithm to compress the enormous scattered migration parameters by B-spline surface fitting: A least surface is fitted by B-spline function which covers all the scattered data according to their coordinate range in 2D plane firstly. Then, on the basis of the linear interpolaton of B-spline smoothing function, the values of all the regular grids can be calculated by solving a liner system equation group with LU decomposition based on the multi-frontal method. Through storing these values of the regular grids, the value of every point from the original data can be estimated. In this way, the aim of scattered data compressing is achieved. The algorithm is practiced successfully in several models. The experiments show that the cubic B-spline function can be the best basal function for surface fitting because it makes the construction surface smooth, as well as has stable and effective compression with high approximate accuracy using regular grids. The compression algorithm has local relative errors as little as 0.0001, compressing ratio up to 300 and faster calculation efficiency than conventional iterative compressing methods. The algorithm is applicable for any seismic data with low gradient.
Efficient data compression for seismic-while-drilling applications
Seismic-while-drilling services efficiently support drilling decisions. They use the vibrations produced by the drill-bit during perforation as a downhole seismic source. The seismic signal is recorded by sensors on the surface, and it is processed in order to obtain/update an image of the subsurface around the borehole. To improve the characterization of the source, some sensors have been experimentally installed also downhole, on the drill pipes in close proximity to the bit: data logged downhole have been able to give better quality information. Currently, the main drawback of downhole equipment is the absence of a high-bit-rate telemetry system to enable real-time activities. This problem may be solved by employing either an offline solution, with limited memory capacity up to few hundreds of megabytes, or an online solution with telemetry at a very low bit-rate (few bits per second). However, following the offline approach with standard acquisition parameters, the internal storage memory would be filled up in just a few hours at high acquisition rates. On the contrary, with the online solution, only a small portion of the acquired signals (or only alarm information about potentially dangerous events) can be transmitted in real time to the surface by using conventional mud-pulse telemetry. We present a lossy data compression algorithm based on a new representation of downhole data in angle domain, which is suitable for downhole implementation and may be successfully applied to both online and offline solutions. Numerical tests based on real field data achieve compression ratios up to 112:1 without major loss of information. This allows a significant increase in downhole time acquisition and in real-time information that can be transmitted through mud-pulse telemetry.
Drillstring Imaging: An Interpretation of Surface Drilling Vibrations
A brief review of drillstring vibration literature is followed by the development of a model-based approach to analyze drillstring vibrations. The resulting image calculated from vibration data allows identification of interaction points between the wellbore and the drillstring. Field data examples are given.