Compression of Downhole Data

Bernasconi, G.; Rampa, Vittorio; Abramo, F.; Bertelli, L.

doi:10.2118/52806-ms

Cited by 10 publications

(5 citation statements)

References 10 publications

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“…Applications, in the oil industry, comprise the preadjustment, filtering, and anomaly identification of pressure tests (Jansen and Kelkar, 1997;Athichanagorn et al, 1999;Gonzalez et al, 1999;Soliman et al, 2001), compression-transmission of drilling data (logging while drilling) (Bernasconi et al, 1999).…”

Section: Theoretical Background Of Wavelet Transformmentioning

confidence: 99%

“…In particular, the wavelet based multiscale analysis of GWL has been developed (Prokoph and Agterberg, 2000;Bernasconi et al, 1999 ), and represents opportunities for research and technologic development, which, combined with structural and stratigraphic seismic interpretation, will contribute to the different stages of reservoir characterization.…”

Section: Introductionmentioning

confidence: 99%

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Multi-scale analysis of well-logging data in petrophysical and stratigraphic correlation

Coconi-Morales

Ronquillo-Jarillo

Campos-Enríquez

2010

GeofInt

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Determinación de los límites locales de una columna estratigráfica (por ejemplo relacionados con ambientes de depósito) representan en particular una gran contribución al análisis y caracterización de yacimientos petroleros. En este marco general, las Transformadas de Ondícula, continua y discreta, son aplicadas a datos de registros geofísicos de pozos de un área productora de aceite en el Golfo de México, con el propósito de encontrar periodicidades o ciclos y correlacionarlos con las características litológicas y estratigráficas de los ambientes asociados. Un análisis multiescala de registros geofísicos de pozos (rayos gama, resistividad y potencial espontáneo) fue realizado basado en la transformada de ondicular. En particular los coeficientes ondiculares fueron determinados. El análisis de los escalogramas-espectrogramas permitió obtener pseudolongitudes de onda características para cada escala (frecuencias). Las pseudolongitudes de onda fueron asociadas con posibles periodicidades o periodos deposicionales (ciclos climáticos de Milankovitch) del área de estudio. El caso presentado muestra que el análisis ondicular es una técnica complementaria de gran ayuda para la caracterización de yacimientos, particularmente en la localización de secuencias estratigráficas y de las facies asociadas.

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Section: Theoretical Background Of Wavelet Transformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-scale analysis of well-logging data in petrophysical and stratigraphic correlation

Coconi-Morales

Ronquillo-Jarillo

Campos-Enríquez

2010

GeofInt

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“…Bernasconi, et al 23 presented a data compression algorithm based on the wavelet transform. They studied the possibility of compressing the downhole data using a waveletbased compression algorithm that was able to maintain high quality in the stored signals.…”

Section: Downhole Data Compressionmentioning

confidence: 99%

Wavelets in Petroleum Industry: Past, Present and Future

Guan

2004

SPE Annual Technical Conference and Exhibition

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractWavelet is first introduced by Alfred Haar in 1910, but the development of wavelet was very slow until the middle of 1980s. In 1984, Jean Morlet made the wavelet rebirth by developing a new way of analyzing the seismic signals to overcome the deficiencies in the Fourier method. Since then, the new developments of wavelets have fascinated the scientific and engineering communities.A wavelet is a waveform of effectively limited duration that has an average value of zero and wavelets are a family of basis functions, which can separate a signal into distinct frequency packets that are localized in the time domain. Thus, wavelets are well suited to analyze nonstationary data. They can smooth the basic signals and keep the details of basic signals. Therefore, they provide a multiresolution framework for data representation.Wavelet analysis is a rapidly developing area in many disciplines of science and engineering and it is used in a wide variety of applications in the areas of medicine, biology, data compression, etc. In recent years, wavelet analysis has found its application in the petroleum industry. This paper reviews the recent application of wavelet analysis in the industry.Various application examples are discussed, especially the examples in the areas of reservoir characterization, geological model upscaling, and well testing. simple digital filter ideas, shown in Fig.1. Thanks to Daubechies' work, wavelet transform has been widely used in many fields such as pattern recognition, image compression, mechanical fault diagnostic, signal de-noising, signal compression, earthquake diction, and other areas since 1990s.

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“…Bernasconi, et al 19 , presented a lossy data compression algorithm based on the wavelet transform (WT) and found it was suitable for downhole implementation and might be successfully applied both online and offline solutions to the data compression for measurement while drilling (MWD).…”

Section: Downhole Data Compressionmentioning

confidence: 99%

Review of the Application of Wavelet Analysis in the Petroleum Industry

Guan¹,

Du²

2004

Canadian International Petroleum Conference

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Wavelet transforms are a family of basis functions that separate a function of a signal into distinct frequency packets that are localized in the time domain. Thus, wavelets are well suited for analyzing nonstationary data. It can smooth the basic signals and keep and even enhance of details. So it provides a multiresolution framework for data representation.Wavelet transform is now used in a wide variety of applications in the areas of medicine, biology, data compression, etc. In recent years, wavelet analysis is increasingly applied to the data analysis in petroleum industry. This paper reviews the recent application of the wavelet transform methodologies to data analysis in petroleum industry, especially the application in reservoir engineering fields. Various field examples are provided to demonstrate the applications of wavelet transform in petroleum industry, especially in the areas of well testing, well logging, seismic, and petroleum geology.

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Compression of Downhole Data

Abstract: This paper was prepared for presentation at the 1999 SPE/IADC Drilling Conference held in Amsterdam, Holland, 9-11 March 1999.

Cited by 10 publications

References 10 publications

Multi-scale analysis of well-logging data in petrophysical and stratigraphic correlation

Multi-scale analysis of well-logging data in petrophysical and stratigraphic correlation

Wavelets in Petroleum Industry: Past, Present and Future

Review of the Application of Wavelet Analysis in the Petroleum Industry

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