發(fā)布時間：2018-05-05 14:27

  本文選題：S變換 + 廣義S變換　； 參考：《西安石油大學(xué)》2017年碩士論文

【摘要】：地球物理測井在石油及煤田勘探和開發(fā)中一直占據(jù)主導(dǎo)作用,基于常規(guī)測井曲線已經(jīng)完成許多地質(zhì)解釋及評價工作。一般對于常規(guī)測井曲線的處理是基于形態(tài)和幅值的視覺域完成的,但是對測井信息包涵的不同深頻信息難以處理。為了進(jìn)一步對測井曲線的深頻信息進(jìn)行挖掘,近年來,眾多學(xué)者將時頻分析技術(shù)應(yīng)用于常規(guī)測井曲線處理研究中,取得了很好的應(yīng)用效果。因此,本文提出基于廣義S變換的常規(guī)測井曲線應(yīng)用研究。本文首先介紹了S變換及廣義S變換的國內(nèi)外研究及應(yīng)用現(xiàn)狀,對S變換及廣義S變換的理論進(jìn)行了系統(tǒng)的闡述,梳理和總結(jié)了S變換及廣義S變換的性質(zhì),對比分析了S變換及廣義S變換的結(jié)果。通過對構(gòu)建的仿真信號進(jìn)行研究,結(jié)果表明,S變換及廣義S變換具有局部分析特性、時移性、無損可逆性及很好的時頻分辨率等特性,而廣義S變換相比S變換具有更好的時頻聚焦性。將廣義S變換應(yīng)用于常規(guī)測井曲線的處理與解釋之中。構(gòu)建仿真信號進(jìn)行了高頻信號去噪處理,基于廣義S變換在深-頻譜中對實際測井資料進(jìn)行了去噪分析與處理,結(jié)果表明,去噪效果較好;對測井薄層模型進(jìn)行分析,基于廣義S變換在深-頻譜中對實際測井資料進(jìn)行薄層的識別與劃分,結(jié)果表明,劃分結(jié)果與實際測井資料匹配一致;構(gòu)建了正旋回、反旋回測井模型,并對其進(jìn)行分析,基于廣義S變換在深-頻譜中對實際測井資料進(jìn)行沉積旋回的識別與劃分,結(jié)果表明,劃分結(jié)果與實際測井資料匹配一致。因此,以上研究成果說明了廣義S變換具有很好的時頻(深頻)分辨率、多分辨率及局部頻譜分析等特征,對于常規(guī)測井曲線的處理和解釋具有重要的指導(dǎo)意義。
[Abstract]:Geophysical logging has always played a leading role in exploration and development of petroleum and coal fields, and many geological interpretation and evaluation work have been completed based on conventional logging curves. Generally, the processing of conventional logging curves is based on the visual domain of shape and amplitude, but it is difficult to deal with the different deep frequency information contained in logging information. In order to further mine the deep frequency information of logging curves, many scholars have applied time-frequency analysis technology to the research of conventional log curve processing in recent years, and achieved good results. Therefore, this paper presents a general well logging curve application research based on generalized S transform. In this paper, the research and application of S transform and generalized S transform are introduced, and the theory of S transform and generalized S transformation are systematically expounded, and the properties of S transform and generalized S transform are summarized. The results of S-transform and generalized S-transform are compared and analyzed. Through the research of the simulated signal, the results show that the S transform and the generalized S transform have the characteristics of local analysis, time shift, lossless reversibility and good time-frequency resolution, etc. The generalized S transform has better time frequency focusing than S transform. The generalized S-transform is applied to the processing and interpretation of conventional logging curves. The simulated signal is de-noised by high-frequency signal, and the actual logging data are analyzed and processed based on the generalized S-transform. The results show that the de-noising effect is good, and the model of logging thin layer is analyzed. Based on the generalized S transform, the actual logging data are identified and partitioned in the deep spectrum. The results show that the partition results are consistent with the actual logging data, and the positive cycle and inverse cycle logging models are constructed and analyzed. Based on the generalized S transform, the actual logging data are identified and partitioned in deep spectrum. The results show that the partition results are consistent with the actual logging data. Therefore, the above research results show that the generalized S-transform has good time-frequency (deep-frequency) resolution, multi-resolution and local spectrum analysis, and has important guiding significance for the processing and interpretation of conventional logging curves.
【學(xué)位授予單位】：西安石油大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：P631.81

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本文編號：1848041