本文選題：雜鹵石 + 支持向量機(jī)　； 參考：《地球科學(xué)進(jìn)展》2016年10期

【摘要】：雜鹵石是四川盆地主要的固態(tài)鉀礦物,川中地區(qū)大多數(shù)雜鹵石層不純,通常伴隨石膏層、硬石膏層、鹽巖層發(fā)育,甚至同層沉積,常規(guī)測(cè)井解釋方法只能粗略地識(shí)別雜鹵石層。以支持向量機(jī)理論和測(cè)井解釋為基礎(chǔ),測(cè)井?dāng)?shù)據(jù)作為輸入,構(gòu)建預(yù)測(cè)模型,對(duì)川中地區(qū)下中三疊統(tǒng)雜鹵石樣本做精細(xì)識(shí)別,將識(shí)別結(jié)果與錄井資料驗(yàn)證對(duì)比,正確率達(dá)到90%以上。再以預(yù)測(cè)模型為基礎(chǔ),結(jié)合含雜鹵石巖性在測(cè)井曲線(xiàn)上的響應(yīng)情況,構(gòu)建雜鹵石層分類(lèi)識(shí)別模型,識(shí)別雜鹵石層、石膏質(zhì)雜鹵石層和雜鹵石膏巖層,識(shí)別正確率達(dá)到91.78%,與常規(guī)測(cè)井解釋方法相比具有明顯優(yōu)勢(shì)。結(jié)果表明,將支持向量機(jī)運(yùn)用到找鉀礦中具有廣闊的前景。
[Abstract]:Complex halite is the main solid potassium mineral in Sichuan basin. Most of the mixed halite layers in central Sichuan are impure, usually accompanied by gypsum layer, anhydrite layer, salt rock formation, and even the same layer deposition. The conventional logging interpretation method can only roughly identify the mixed halite beds. Based on the support vector machine theory and log interpretation, the prediction model is constructed by using log data as input, and fine identification of the lower middle Triassic mixed halogen samples in central Sichuan is made, and the recognition results are verified and compared with the logging data. The accuracy is over 90%. Based on the prediction model, combined with the response of the complex halogenite on the logging curve, the classification and recognition model of the complex halogenite layer is constructed to identify the mixed halite layer, the gypsum mixed halite layer and the complex halogen gypsum stratum. The recognition accuracy is 91.78, which is superior to the conventional logging interpretation method. The results show that the application of support vector machine in potassium prospecting has a broad prospect.
【作者單位】： 西南石油大學(xué)地球科學(xué)與技術(shù)學(xué)院;川慶鉆探工程有限公司地球物理勘探公司;中國(guó)石油新疆油田分公司勘探開(kāi)發(fā)研究院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目“四川盆地油鉀兼探的地球物理評(píng)價(jià)方法研究”(編號(hào):41372103) 國(guó)家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃項(xiàng)目“四川三疊紀(jì)古特提斯海盆鉀分布、評(píng)價(jià)研究”(編號(hào):2011CB403002)資助~~
【分類(lèi)號(hào)】：P619.211

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本文編號(hào)：2092310