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摘要? 現(xiàn)有研究對四川盆地龍馬溪組頁巖壓后各因素影響返排率的機理認(rèn)識不清,，返排率影響產(chǎn)能的規(guī)律不明朗,無法通過控制返排率控制產(chǎn)量，提高單井產(chǎn)量難度大。本研究基于地質(zhì)數(shù)據(jù),、生產(chǎn)數(shù)據(jù)和施工數(shù)據(jù)，選取四川盆地龍馬溪組WH區(qū)塊的泊松比,、黏土含量,、有機碳含量、含氣量、孔隙度,、脆性指數(shù),、地層壓力、層厚作為地質(zhì)因素,，水平段長,、壓裂水平段長、主壓裂用液量,、加砂強度,、施工排量、支撐劑量作為工程因素,，通過建立前饋神經(jīng)網(wǎng)絡(luò)模型,，分析上述兩類因素在預(yù)測頁巖氣井返排率時的影響權(quán)重，發(fā)現(xiàn)泊松比,、孔隙度,、黏土含量以及壓裂水平段長、加砂強度,、施工排量分別為地質(zhì)和工程方面的主控因素,。針對主控因素，應(yīng)用多元非線性擬合,，建立以工程指數(shù)為響應(yīng)值,、返排率與地質(zhì)綜合指數(shù)關(guān)系的預(yù)測圖版；并進一步建立以綜合指數(shù)為響應(yīng)值的返排率與產(chǎn)能關(guān)系圖版,。圖版分析表明,，要注重綜合因素對返排率和產(chǎn)能的影響。通過實際生產(chǎn)數(shù)據(jù)統(tǒng)計發(fā)現(xiàn),，四川盆地頁巖氣井存在最優(yōu)返排率,，達(dá)到最優(yōu)返排率可以使頁巖氣井產(chǎn)氣量最大化。本研究建立的返排率預(yù)測圖版可有效預(yù)測返排率,，并通過可控因素最優(yōu)化返排率使其位于產(chǎn)量最大區(qū)間,，進而助力提高頁巖氣井產(chǎn)量。

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關(guān)鍵詞 ：四川盆地；返排率,；前饋神經(jīng)網(wǎng)絡(luò)法,；最優(yōu)返排率；多因素分析,；定量預(yù)測

Abstract：

The mechanism of the factors affecting the flowback ratio after fracturing in the Longmaxi Formation in the Sichuan Basin is unclear. The mechanisms by which the flowback ratio affects the productive capacity are also unclear and increasing single well production is difficult. For this purpose, based on geological data, production data and construction data, this study selects Poisson's ratio, clay content, total organic carbon content (TOC), gas content, porosity, brittleness index, formation pressure,and layer thickness of the WH block of the Longmaxi Formation in the Sichuan Basin as the geological factors. The length of the horizontal section, the length of the fracturing section, the amount of liquid used for the main fracturing, the strength of the sand reinforcement, the construction displacement, and the supporting dose are selected as the engineering factors. By establishing a proper BP neural network model, the weights of these factors affecting the prediction of shale gas well flowback ratio are analyzed. It is found that Poisson's ratio, porosity, clay content, the length of the fracturing section, the strength of the sand reinforcement, and the construction displacement are the main controlling factors in geology and engineering. For the main controlling factors, a multivariate nonlinear fitting is applied to establish a prediction template with the engineering index as the response value based on the relationship between the flowback ratio and the geological comprehensive index, and a template of the relationship between the flowback ratio and the productive capacity with the comprehensive index as the response value is further established. The analysis shows that it is necessary to pay attention to the impact of comprehensive factors on the flowback ratio and productive capacity. According to the statistics of production data, it is found that the shale gas well in the Sichuan Basin has an optimum flowback ratio, and the optimum flowback ratio can maximize the gas production of the shale gas well. The flowback ratio prediction template established in this study can effectively predict and optimize the flowback ratio,thereby helping to improve the production of shale gas wells.

Key words： Sichuan Basin; flowback ratio; Back Propagation (BP) neural network; the optimum flowback ratio; multi-factor analysis; quantitative forecast

收稿日期: 2019-09-29 ????

PACS:

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基金資助:國家科技重大專項“大型油氣田及煤層氣開發(fā)”課題4“頁巖氣排采工藝技術(shù)與應(yīng)用”( 編號：2017ZX05037-004) 資助

通訊作者: [email protected]

引用本文: ??

郭建成, 林伯韜, 向建華, 鐘華. 四川盆地龍馬溪組頁巖壓后返排率及產(chǎn)能影響因素分析. 石油科學(xué)通報, 2019, 03: 273-287

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GUO Jiancheng, LIN Botao, XIANG Jianhua, ZHONG Hua. Study of factors affecting the flowback ratio and productive capacity of Longmaxi Formation shale in the Sichuan basin after fracturing. Petroleum Science Bulletin, 2019, 03: 273-287.

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