Identification of Diagenetic Facies Logging of Tight Oil Reservoirs Based on Deep Learning—A Case Study in the Permian Lucaogou Formation of the Jimsar Sag, Junggar Basin

Abstract

As a typical tight oil reservoir in a lake basin, the Permian Lucaogou Formation of the Jimsar Sag in the Junggar Basin has great potential for exploration and development. However, at present, there are few studies on the identification of the diagenetic facies of tight oil reservoir logging in the study area, and the control effect of diagenesis on tight oil reservoirs is not clear. The present work investigates the diagenesis and diagenetic facies logging of the study area, making full use of core data, thin sections, and logs, among other data, in order to understand the reservoir characteristics of the Permian Lucaogou Formation in the Jimsar Sag. The results show that the Lucaogou Formation has undergone diagenetic activity such as compaction, carbonate cementation, quartz cementation, and clay mineral infilling and dissolution. The diagenetic facies are classified according to mineral and diagenetic type, namely, tightly compacted facies, carbonate-cemented facies, clay mineral-filling facies, quartz-cemented facies, and dissolution facies. The GR, RT, AC, DEN, and CNL logging curves were selected, among others, and the convolutional neural network was introduced to construct a diagenetic facies logging recognition model. The diagenetic facies of a single well was divided and identified, and the predicted diagenetic facies types were compared with thin sections and SEM images of the corresponding depths. Prediction results had a high coincidence rate, which indicates that the model is of a certain significance to accurately identify the diagenetic facies of tight oil reservoirs. Assessing the physical properties of the studied reservoirs, dissolution facies are the dominant diagenetic facies in the study area and are also the preferred sequence for exploration—to find dominant reservoirs in the following stage.

Determination of the Lower Limit of Physical Properties of Tight Oil Reservoirs: A Case Study of the Lower Es3 in the Jiangjiadian Area, Linnan Sag

“…The present burial depth of the lower E s 3 in Linnan Sag is 1600–3500 m, which belongs to the stage of middle diagenetic evolution . Compaction and cementation will have an impact on reservoir porosity, which is destructive diagenesis . The dissolution is mainly caused by the dissolution of various soluble components such as feldspar and debris in the skeleton particles, which can increase the pore space of the reservoir and improve the quality of the reservoir …”

“… 38 The dissolution is mainly caused by the dissolution of various soluble components such as feldspar and debris in the skeleton particles, which can increase the pore space of the reservoir and improve the quality of the reservoir. 38 …”

“…7 Compaction and cementation will have an impact on reservoir porosity, which is destructive diagenesis. 38 The dissolution is mainly caused by the dissolution of various soluble components such as feldspar and debris in the skeleton particles, which can increase the pore space of the reservoir and improve the quality of the reservoir. 38 Compaction runs through the whole diagenesis process, resulting in the destruction of a large number of primary pores in the reservoir and the deterioration of the reservoir's physical properties.…”

“…38 The dissolution is mainly caused by the dissolution of various soluble components such as feldspar and debris in the skeleton particles, which can increase the pore space of the reservoir and improve the quality of the reservoir. 38 Compaction runs through the whole diagenesis process, resulting in the destruction of a large number of primary pores in the reservoir and the deterioration of the reservoir's physical properties. The microscopic sections of rock samples in the lower Es 3 in the Jiangjiadian area show that compaction is generally developed.…”

Intelligent Identification Method for the Diagenetic Facies of Tight Oil Reservoirs Based on Hybrid Intelligence—A Case Study of Fuyu Reservoir in Sanzhao Sag of Songliao Basin

“…China's tight oil reservoirs are mainly distributed in Songliao Basin, Ordos Basin, Bohai Bay Basin and Junggar Basin [3,4]. Tight oil reservoirs are deeply buried and have the characteristics of coexistence of source rock and reservoir, low porosity and low permeability, complex pore structure and strong heterogeneity after complex diagenetic processes [5][6][7][8][9]. The analysis of the influence of diagenetic change on reservoir quality can effectively guide the exploration and development of tight oil reservoirs, so the study of diagenetic facies 2 of 20 is of great significance for the quality evaluation of tight oil reservoirs and "sweet spots" prediction [10,11].…”