【摘要】：隨著世界各國對能源需求的不斷增長,開發(fā)高含硫氣田有助于緩解能源緊張的局面,其在整個天然氣工業(yè)中的地位也將越來越突出。與常規(guī)天然氣相比,高含硫天然氣不僅具有極強的腐蝕性和劇毒性,還具有特殊的PVT性質(zhì)以及獨特的相態(tài)變化特征。高含硫天然氣在集輸過程中,隨著壓力、溫度等條件的變化,溶解在氣體中的元素硫可能會在集輸管道中以固體顆粒形態(tài)析出并發(fā)生沉積。硫沉積會造成地面集輸管道出現(xiàn)“硫堵”,引起鋼材的腐蝕,最終影響氣體的正常輸送。因此,研究集輸管道中的硫沉積對于保障高含硫天然氣安全、高效地集輸至關重要。本文主要針對高含硫天然氣集輸管道硫沉積預測方法這一問題展開研究,主要完成了以下工作： (1)研究元素硫在集輸管道中沉積的機理有助于弄明白硫沉積發(fā)生的本質(zhì),同時也是建立集輸管道硫沉積預測模型的基礎和前提。為此,首先對元素硫的存在形式、密度、黏度、比熱和凝固點變化規(guī)律等物理性質(zhì)進行了定性分析和定量研究。然后對計算高含硫天然氣物性參數(shù)的方法進行了優(yōu)選,得到：DPR模型結合WA校正法是計算高含硫天然氣壓縮因子的最佳方法,同時BWRS狀態(tài)方程計算壓縮因子時也具有較高的精度；Dempsey模型結合Standing校正法是計算高含硫天然氣黏度的最佳方法。在此基礎上,明確了硫化氫是元素硫來源的物質(zhì)基礎,根據(jù)化學反應平衡原理確定了元素硫的溶解與沉積主要以物理溶解與沉積為主。元素硫的沉積主要考慮溶解度的變化,而壓力、溫度和氣體組分是影響元素硫溶解度的主要因素。 (2)分析評價了現(xiàn)有典型預測硫在高含硫氣體中溶解度方法的適用性和局限性,在此基礎上,提出運用遺傳算法結合BP神經(jīng)網(wǎng)絡預測硫在高含硫氣體中的溶解度。設計了該模型的計算步驟,討論了該模型的參數(shù)設置,并對該模型進行了測試和驗證,結果表明遺傳BP神經(jīng)網(wǎng)絡預測模型的精度較高。 (3)根據(jù)水平管道中氣固運移特征和氣固兩相流動理論,對管道內(nèi)析出的固體硫顆粒進行了受力分析,應用固體顆粒群臨界流速計算模型分析了元素硫固體顆粒在管道中發(fā)生沉積的條件。運用FLUENT軟件中的RSM模型和DPM模型研究了析出位置不立即發(fā)生沉積的硫顆粒在直管段、水平彎管以及閥門等處的運移沉降規(guī)律,硫顆粒在直管段中的沉積率隨著氣流流速的增大而減小,隨著顆粒直徑的增大而增大；硫顆粒在水平彎管中的沉積率隨氣流流速、顆粒直徑和彎曲比的增大而增大；硫顆粒在閥門處的沉積率隨氣流流速和顆粒直徑的增大而增大,隨閥門開度的增大而減小。 (4)基于(1)～(3)的研究成果,結合高含硫天然氣集輸管道壓力溫度分布預測模型,建立了高含硫天然氣集輸管道硫析出位置、硫沉積條件判定以及硫沉積量計算的預測模型,并運用這些模型對國內(nèi)某高含硫氣田集輸管道的硫沉積問題進行了分析,結果表明,模型預測結果與實際較為吻合。
[Abstract]:With the increasing demand for energy in the world, the development of high-sulfur gas fields will help to alleviate the energy shortage and play a more and more important role in the natural gas industry. The elemental sulfur dissolved in the gas may precipitate and deposit in the form of solid particles in the gathering and transportation pipeline with the change of pressure and temperature. Sulfur deposition will cause "sulfur plugging" in the surface gathering and transportation pipeline, resulting in corrosion of steel and ultimately affecting the normal transportation of gas. Therefore, it is very important to study the sulfur deposition in gas gathering and transportation pipelines for ensuring the safety and efficient transportation of high sulfur-bearing natural gas.
(1) Studying the mechanism of elemental sulfur deposition in gathering and transportation pipelines is helpful to understand the nature of sulfur deposition, and it is also the basis and prerequisite for establishing a prediction model of sulfur deposition in gathering and transportation pipelines. The DPR model combined with WA correction method is the best method for calculating the compressibility factor of high sulfur natural gas, and the BWRS equation of state has higher accuracy in calculating the compressibility factor; Dempsey model combined with Standing correction method is the best method for calculating high sulfur natural gas. On this basis, it is clear that hydrogen sulfide is the material basis for the source of elemental sulfur. According to the principle of chemical reaction equilibrium, the dissolution and deposition of elemental sulfur are mainly physical dissolution and deposition. The main factors of degree.
(2) The applicability and limitation of the existing typical methods for predicting the solubility of sulfur in high sulfur gas are analyzed and evaluated. On this basis, a genetic algorithm combined with BP neural network is proposed to predict the solubility of sulfur in high sulfur gas. The results show that the prediction accuracy of genetic BP neural network is high.
(3) According to the characteristics of gas-solid migration and the theory of gas-solid two-phase flow in horizontal pipeline, the force of solid sulfur particles precipitated in pipeline is analyzed, and the condition of elemental sulfur particles deposited in pipeline is analyzed by using the critical velocity calculation model of solid particles. The precipitation is studied by using RSM model and DPM model of FLUENT software. The deposition rate of sulfur particles in straight pipe section decreases with the increase of gas flow velocity and increases with the increase of particle diameter. The deposition rate of sulfur particles in horizontal curved pipe increases with gas flow velocity, particle diameter and bending ratio. The deposition rate of sulfur particles increases with the increase of flow velocity and particle diameter, and decreases with the increase of valve opening.
(4) Based on the research results of (1) ~ (3), combined with the pressure and temperature distribution prediction model of high sulfur gas gathering pipeline, the prediction models of sulfur precipitation location, sulfur deposition condition determination and sulfur deposition calculation of high sulfur gas gathering pipeline are established, and these models are used to solve the sulfur deposition problem of a high sulfur gas gathering pipeline in China. The results show that the prediction results are in good agreement with the actual situation.
【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】：TE86

【參考文獻】

相關期刊論文 前10條

1 寧英男,張海燕,劉春天,劉玉華;Dean-Stiel粘度模型的改進[J];大慶石油學院學報;1999年02期

2 里群，谷明星，陳衛(wèi)東，，鄒向陽，郭天民;富硫化氫酸性天然氣相態(tài)行為的實驗測定和模型預測[J];高校化學工程學報;1994年03期

3 高大文,王鵬,蔡臻超;人工神經(jīng)網(wǎng)絡中隱含層節(jié)點與訓練次數(shù)的優(yōu)化[J];哈爾濱工業(yè)大學學報;2003年02期

4 谷明星,里群,陳衛(wèi)東,郭天民;固體硫在超臨界/近臨界酸性流體中的溶解度(Ⅱ)熱力學模型[J];化工學報;1993年03期

5 上海海運學院起重運輸機械教研組氣力運輸小組;氣力輸送中懸浮速度的理論與實踐[J];化學工程;1977年06期

6 呂子劍,曹文仲,劉今,吳若瓊;不同粒徑固體顆粒的懸浮速度計算及測試[J];化學工程;1997年05期

7 關光森;章琛;翟慶良;;兩相流管道中顆粒懸浮速度理論公式及其實驗驗證[J];洛陽工學院學報;1983年01期

8 胡德棟;王威強;魏東;郭建章;;固體在超臨界流體中溶解度的BP人工神經(jīng)網(wǎng)絡模擬[J];山東大學學報(工學版);2006年02期

9 卞小強;杜志敏;陳靜;李明軍;;一種關聯(lián)元素硫在酸性氣體中的溶解度新模型[J];石油學報(石油加工);2009年06期

10 郭緒強,閻煒,陳爽,郭天民;特高壓力下天然氣壓縮因子模型應用評價[J];石油大學學報(自然科學版);2000年06期

相關博士學位論文 前1條

1 劉洪濤;氣固兩相流中微細顆粒沉積與擴散特性的數(shù)值研究[D];重慶大學;2010年

本文編號：2200352