本文關(guān)鍵詞： 采注優(yōu)化 推理引擎 Bitmap 規(guī)則匹配 事件過濾　出處：《自動化學(xué)報》2017年06期 　論文類型：期刊論文

【摘要】：針對油田油水井采注優(yōu)化業(yè)務(wù)中,油水井?dāng)?shù)據(jù)量大、地層結(jié)構(gòu)復(fù)雜以及人類經(jīng)驗多的特點,分析了傳統(tǒng)推理方法在油田采注實時優(yōu)化處理過程中的不足,采用事件處理思想,提出了一種基于Bitmap事件編碼與匹配機制的推理引擎,有效地實現(xiàn)了對無效事件的過濾并提升了事件與規(guī)則的匹配效率.在油田實際數(shù)據(jù)試驗平臺上對該方法進行了驗證并與RETE算法、LFA(Linear forward-chaining)算法的性能對比,結(jié)果驗證了本文方法在實時推理能力上的有效性.
[Abstract]:In view of the characteristics of large amount of data, complex formation structure and human experience in oil and water well production and injection optimization in oil field, this paper analyzes the shortcomings of traditional reasoning method in the process of real-time optimization of oilfield production and injection, and adopts the idea of event processing. A reasoning engine based on Bitmap event coding and matching mechanism is proposed. The filter of invalid events is realized effectively and the matching efficiency between event and rule is improved. The method is verified on the platform of oilfield actual data and compared with the performance of RETE algorithm. The results show that the proposed method is effective in real-time reasoning.
【作者單位】： 中國科學(xué)院沈陽自動化研究所工業(yè)控制網(wǎng)絡(luò)與系統(tǒng)研究室;
【基金】：國家自然科學(xué)基金(61533015)資助~~
【分類號】：TE319
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本文編號：1508408