【摘要】：鉆井作業(yè)是石油和天然氣勘探開發(fā)活動中最主要的事故頻發(fā)區(qū)之一。鉆井作業(yè)現(xiàn)場的隱患數(shù)量和人員違章數(shù)量常常居高不下,大量的隱患和人員違章極易誘使安全事故的發(fā)生。安全事故一旦發(fā)生,便會造成人員損失、設備損壞和壞境污染,也會對經(jīng)濟效益和社會效益產(chǎn)生巨大影響。如何保證鉆井作業(yè)的安全進行,預防事故的發(fā)生始終是鉆井作業(yè)行業(yè)需要重點關注的問題。 因而,全面辨識和分析油氣鉆井作業(yè)系統(tǒng)中的危險源,了解鉆井作業(yè)現(xiàn)場的安全狀態(tài)是必要的。建立一套適合油氣鉆井作業(yè)安全評價模型是當前油氣鉆井作業(yè)所急需解決的問題。本文的研究旨在為鉆井作業(yè)的安全評價提供有效的評價方法,為鉆井作業(yè)的安全監(jiān)管人員提供實時、客觀的決策依據(jù)。本文的研究是鉆井作業(yè)安全管理走向科學化、信息化的一種全新探索,對提升鉆井公司的安全管理水平有重大的意義。 油氣鉆井作業(yè)是一個復雜的系統(tǒng)工程,該系統(tǒng)的最大特點是動態(tài)性、隨機性和模糊性。影響鉆井作業(yè)安全的因素眾多,各因素之間相互制約。鉆井作業(yè)進行安全評價是一種非線性問題�？紤]到BP神經(jīng)網(wǎng)絡具有很好的非線性映射能力,粗糙集對不完備和不確定信息的強大分析能力,本文采用粗糙集和神經(jīng)網(wǎng)絡來構建鉆井作業(yè)安全評價模型。本文主要開展一些幾個方面的研究：(1)了解安全評價和鉆井作業(yè)安全評價的國內外研究現(xiàn)狀；(2)綜合辨識鉆井作業(yè)過程中的危險源,從人的不安全行為和物的不安全狀態(tài)兩個方面出發(fā)對其進行分析,建立鉆井作業(yè)安全評價指標體系；(3)使用粗糙集和神經(jīng)網(wǎng)絡的松耦合模型做鉆井作業(yè)安全的定性評價和使用神經(jīng)網(wǎng)絡做鉆井作業(yè)安全的定量評價。在做定性安全評價時,本文首先使用粗糙集對樣本數(shù)據(jù)做屬性約簡。然后,基于最小條件屬性集選取神經(jīng)網(wǎng)絡的訓練樣本和測試樣本。最后,構建神經(jīng)網(wǎng)絡模型,使用訓練樣本對其訓練,使用測試樣本進行預測。之后,本文使用神經(jīng)網(wǎng)絡做了鉆井作業(yè)安全的定量評價,分別使用訓練樣本和測試樣本對網(wǎng)絡進行了訓練和測試；(4)鉆井作業(yè)安全評價模型的設計,主要包括：系統(tǒng)的總體設計,粗糙集模塊的程序設計和神經(jīng)網(wǎng)絡模塊的程序設計。
[Abstract]:Drilling is one of the most important accident-prone areas in oil and gas exploration and development activities. The number of hidden troubles and the number of personnel violating regulations are always high in drilling operation, and a large number of hidden dangers and personnel violations are easy to induce the occurrence of safety accidents. Once a safety accident occurs, it will cause loss of personnel, equipment damage and environmental pollution. It will also have a great impact on economic and social benefits. How to ensure the safety of drilling operation and how to prevent accidents are always the key issues for the drilling industry to pay attention to. Therefore, it is necessary to identify and analyze the hazard sources in the oil and gas drilling system and to understand the safety state of the drilling site. It is an urgent problem to establish a set of safety evaluation model for oil and gas drilling operation. The purpose of this paper is to provide an effective evaluation method for the safety evaluation of drilling operations, and to provide real-time and objective decision basis for the safety supervisors of drilling operations. The research of this paper is a new exploration of drilling operation safety management, which is scientific and information, and has great significance to improve the safety management level of drilling companies. Oil and gas drilling is a complex system engineering, the system is characterized by dynamic, randomness and fuzziness. There are many factors influencing the safety of drilling operation, and each factor restricts each other. Drilling safety evaluation is a nonlinear problem. Considering that BP neural network has good nonlinear mapping ability, rough set has strong ability to analyze incomplete and uncertain information, this paper uses rough set and neural network to construct safety evaluation model of drilling operation. This paper mainly carries out some research in several aspects: (1) to understand the current situation of safety assessment and safety evaluation of drilling operations at home and abroad; (2) identify the dangerous sources in drilling operation synthetically, analyze the unsafe behavior of human and the unsafe state of objects, and establish the evaluation index system of drilling operation safety; (3) the loosely coupled model of rough set and neural network is used to evaluate the safety of drilling operation qualitatively and quantitatively. In the qualitative security evaluation, the rough set is first used for attribute reduction of sample data. Then, the training samples and test samples of neural network are selected based on the minimum conditional attribute set. Finally, the neural network model is constructed, the training sample is used to train it, and the test sample is used to predict it. After that, the neural network is used to evaluate the safety of drilling operation quantitatively, and the network is trained and tested using training samples and test samples respectively. (4) the design of the safety evaluation model of drilling operation mainly includes: the overall design of the system, the programming of the rough set module and the program design of the neural network module.
【學位授予單位】：西南石油大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TE28

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