In order to define a favorable oil and gas accumulation area, this study focused on reservoir recognition which is based on logging data of old wells. The Gaofengchang structure in eastern Sichuan is used as a test area to discuss the necessity and feasibility of curve construction by combining new and old wells. Analysis of the reasons for the inaccuracy of the traditional curve reconstruction method is also provided. Given the interdependence of the well log in the depth domain sample sequence, a new intelligent construction method (BI-LSTM) based on the cyclic neural network is proposed. A discussion on the effect of data increments on prediction accuracy is also provided. The following four conclusions were achieved through curve reconstruction experiments: a high-precision CNL pseudo-curve was obtained; an underdetermined equation in optimization logging interpretation method needed to be extended to a positive definite equation; the quantitative processing of the complex lithologic reservoir parameters for the old wells was realized; and the processing result of the lithology physical property were basically consistent with the core data. Therefore, the BI-LSTM proposed in this paper could improve the accuracy of logging curve construction and has a good promotion significance for the old well review.

Aim at the problems that the genesis and deep dynamic mechanism of Paleozoic-Mesozoic granites in the north western margin of South Altun Mountains have not been analyzed on the whole, systematic petrographic and elemental geochemistry studies on granites in the eastern segment of South Altun Mountains were carried out. The lithology of the area is mainly granite, granodiorite and monzonite, with SiO₂ of 57.35% ~ 88.11%, Al₂O₃ of 3.84%~19.56%, and total alkali content 1.00%~9.92%, with different degrees of Eu (Eu is 0.24~1.04), which belongs to the alkalic-alkali calcic-calc alkalic-calcic series, all of which have the characteristics of peraluminous, enrichment of large ion lithophile elements(LILE) and loss of high field strength elements(HFSE). Based on the results of previous studies and the classification of Sr-Yb, the Palaeo-mesozoic magmatism in this area can be divided into six episode: episode 1 (484-458 Ma) is the Nanling Mountains I-type granite, which may be derived from partial melts of metamorphic basalts; episode 2 (450~406 Ma) is Himalayan and Zhejiang mixed type granites, which have I-S and S type granites respectively, and the source areas are partial melts products of garnet amphibolite and metamorphic mudstone sandstone respectively; episode 3 (404~385 Ma) is the Nanling Mountains A2-type granite, which may be the partial melts product of the granodiorite at low pressure ; episode 4 (380~343 Ma) is the post-collisional uplifts of the Adakite and Zhejiang type granites, which are of type I granite and are related to the crustal detachment;and episode 5 (253~280 Ma) is the Nanling Mountains S type granites, It may be derived from the partial melts of metamorphic mudstone, which is the product of the closure of the Tethys Ocean; episode 6(154 ~ 230 Ma) is Himalayan I-type granite, and the source area is the partial melts product of meta-sandstone, which is related to subduction of residual ocean basin.