發(fā)布時(shí)間：2018-05-20 13:15

  本文選題：氣測(cè)錄井 + 校正處理　； 參考：《東北石油大學(xué)》2015年碩士論文

【摘要】：在現(xiàn)代鉆井工藝中,工作人員主要通過儀器對(duì)鉆井產(chǎn)生的各項(xiàng)信息進(jìn)行采集、分析,由此了解所鉆進(jìn)區(qū)域的地質(zhì)構(gòu)造情況。隨著科技的進(jìn)步與鉆井工藝的不斷完善,此項(xiàng)技術(shù)逐漸演變成錄井技術(shù),到目前為止錄井技術(shù)已經(jīng)成為獲取此類數(shù)據(jù)的重要手段。通過檢測(cè)氣測(cè)錄井?dāng)?shù)據(jù),工作人員不但可隨時(shí)監(jiān)控井下情況,還可以對(duì)所鉆進(jìn)的儲(chǔ)層流體性質(zhì)進(jìn)行判別,判斷哪些是油層、哪些是氣層等,此項(xiàng)工藝稱為氣測(cè)油氣層判別技術(shù)。當(dāng)前采用的氣測(cè)油氣層判別工藝普遍存在兩大弊端,其一是氣測(cè)數(shù)據(jù)易受很多外在因素影響,所以采用的氣測(cè)數(shù)據(jù)都非最初數(shù)據(jù),因此降低了對(duì)儲(chǔ)層判別的準(zhǔn)確率。其二是在現(xiàn)代的氣測(cè)油氣層判別方法中,大多都是人工判別方法,在判別結(jié)果中人為干擾因素起主導(dǎo)作用,包括氣測(cè)費(fèi)歇爾與氣測(cè)貝葉斯油氣層判別方法也存在判別結(jié)果無(wú)法細(xì)化與建模時(shí)間較長(zhǎng)兩種缺陷。因此,本文提出了氣測(cè)錄井?dāng)?shù)據(jù)校正處理方法與基于BP神經(jīng)網(wǎng)絡(luò)的氣測(cè)油氣層判別方法。首先,研究影響氣測(cè)數(shù)據(jù)準(zhǔn)確性的每種因素,將其分為地質(zhì)環(huán)境因素與設(shè)備影響因素兩大類,并且針對(duì)每種影響因素提出相應(yīng)的氣測(cè)數(shù)據(jù)校正處理方法,將儀器所記錄的氣測(cè)數(shù)據(jù)盡可能恢復(fù)到最初狀態(tài)。其次,采用氣測(cè)數(shù)據(jù)與BP神經(jīng)網(wǎng)絡(luò)相結(jié)合的方法,建立氣測(cè)BP油氣層判別網(wǎng)絡(luò)模型。針對(duì)BP神經(jīng)網(wǎng)絡(luò)在建模階段易出現(xiàn)陷入局部最小值的問題,提出一種改進(jìn)的自適應(yīng)學(xué)習(xí)效率方法應(yīng)用于網(wǎng)絡(luò)模型當(dāng)中,減少了氣測(cè)BP油氣層判別網(wǎng)絡(luò)模型訓(xùn)練時(shí)間,提高了工作效率。對(duì)改進(jìn)的氣測(cè)BP油氣層判別方法進(jìn)行應(yīng)用測(cè)試。以一組未知判別結(jié)果的氣測(cè)數(shù)據(jù)作為樣本數(shù)據(jù),首先用氣測(cè)數(shù)據(jù)校正處理方法對(duì)其進(jìn)行校正處理,提高數(shù)據(jù)的準(zhǔn)確性去除環(huán)境因素的影響,然后分別采用改進(jìn)的氣測(cè)BP油氣層判別方法和三角判別方法對(duì)其進(jìn)行判別,根據(jù)后期的試油結(jié)論與判別結(jié)果進(jìn)行對(duì)比,可以看出改進(jìn)的氣測(cè)油氣層判別方法比三角判別方法具有更高的準(zhǔn)確率。
[Abstract]:In modern drilling technology, the workers collect and analyze the information generated by drilling mainly through instruments, and then understand the geological structure of the drilling area. With the progress of science and technology and the continuous improvement of drilling technology, this technology has gradually evolved into a mud logging technology, so far logging technology has become an important means to obtain this kind of data. By detecting the gas logging data, the workers can not only monitor the downhole situation at any time, but also judge the fluid properties of the drilled reservoir, and judge which is the oil layer and which is the gas reservoir. This process is called gas logging oil and gas reservoir discrimination technology. There are two disadvantages in the current gas reservoir identification technology. One is that the gas data are easily affected by many external factors, so the gas data used are not the initial data, so the accuracy of reservoir discrimination is reduced. The other is that most of the modern discriminant methods for gas-bearing oil and gas reservoirs are artificial ones, which play a leading role in discriminating results by human interference factors. There are also two defects in the discriminant method, which include gas measurement Fischer and gas Bayesian oil and gas reservoir discrimination, which can not be refined and the modeling time is longer. Therefore, the method of gas logging data correction and BP neural network is put forward in this paper. First of all, every factor affecting the accuracy of gas data is studied, which is divided into two categories: geological environment factor and equipment influence factor, and the corresponding correction and processing method of gas survey data is put forward for each kind of influence factor. Restore the gas data recorded by the instrument to its original state as far as possible. Secondly, using the method of combining gas data with BP neural network, the model of BP oil and gas reservoir discriminant network is established. In view of the problem that BP neural network is prone to fall into local minimum in the modeling stage, an improved adaptive learning efficiency method is proposed to apply to the network model, which reduces the training time of BP oil and gas layer discriminant network model. Improved working efficiency. The application test of improved BP oil and gas reservoir discrimination method is carried out. Taking a set of gas data of unknown discriminant result as sample data, the method of gas data correction and processing is used to correct the data, and the accuracy of the data is improved to remove the influence of environmental factors. Then the improved BP oil and gas reservoir discrimination method and the triangle discriminant method are used to distinguish them, and the results are compared according to the later oil test results. It can be seen that the improved method has higher accuracy than the triangle method.
【學(xué)位授予單位】：東北石油大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TE142

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本文編號(hào)：1914757