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Percolation Characteristics and Fluid Movability Analysis in Tight Sandstone Oil Reservoirs.

ABSTRACT: The development of tight oil has started relatively late, and the flow mechanisms and fluid movability are still research spotlights. The goal of this paper is to investigate the percolation characteristics and fluid movability of the Chang 6 tight sandstone oil layer in the Upper Triassic Yanchang Formation, Ordos Basin, China. Results show that (1) at low flow velocity, the percolation curve of flow velocity vs pressure gradient is a concave-up nonlinear curve and does not pass through the origin. It is more difficult for oil flow than water flow in cores with similar permeability due to rock wettability and fluid apparent mobility. The application of back pressure makes the nonlinear stage eliminated and the percolation character improved. (2) Two-phase flow tests reveal that oil-phase permeability decreases faster in samples with lower permeability, and the coexistent flow region of oil and water is relatively narrow. The contribution of oil recovery mainly happens at the early stage. The permeability at the isotonic point reduces with the decrease of sample permeability. (3) Flow during water flooding can be roughly divided into four stages according to the injection pressure and flow change. The injection pressure experiences stages of increasing to a peak, then decreasing, and finally becoming stable, accompanied by an increase of oil production until water breaks through. (4) The pore throats of the target reservoir mainly range from 0.001 to 10 ?m, and the bound water mainly distributes in pores less than 0.2 ?m. The irreducible water saturation is 30-35%, and the movable fluid saturation is 65-70%, mainly distributed in pores at 0.2-10.0 ?m with a maximum of 2.0 ?m. The results will supplement the existing knowledge of percolation characters and fluid movability in tight sandstone oil reservoirs.

SUBMITTER: Liu X

PROVIDER: S-EPMC7315431 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Percolation Characteristics and Fluid Movability Analysis in Tight Sandstone Oil Reservoirs.

Liu Xuefen X Kang Yili Y Li Jianfeng J Chen Zhanjun Z Ji Anzhao A Xu Hongwu H

ACS omega 20200610 24

The development of tight oil has started relatively late, and the flow mechanisms and fluid movability are still research spotlights. The goal of this paper is to investigate the percolation characteristics and fluid movability of the Chang 6 tight sandstone oil layer in the Upper Triassic Yanchang Formation, Ordos Basin, China. Results show that (1) at low flow velocity, the percolation curve of flow velocity vs pressure gradient is a concave-up nonlinear curve and does not pass through the ori ...[more]

PMID: 32596569

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Project description:Low salinity waterflooding (LSWF) and its variants also known as smart water or ion tuned water injection have emerged as promising enhanced oil recovery (EOR) methods. LSWF is a complex process controlled by several mechanisms and parameters involving oil, brine, and rock composition. The major mechanisms and processes controlling LSWF are still being debated in the literature. Thus, the establishment of an approach that relates these parameters to the final recovery factor (RFf) is vital. The main objective of this research work was to use a number of artificial intelligence models to develop robust predictive models based on experimental data and main parameters controlling the LSWF determined through sensitivity analysis and feature selection. The parameters include properties of oil, rock, injected brine, and connate water. Different operational parameters were considered to increase the model accuracy as well. After collecting the relevant data from 99 experimental studies reported in the literature, the database underwent a comprehensive and rigorous data preprocessing stage, which included removal of duplicates and low-variance features, missing value imputation, collinearity assessment, data characteristic assessment, outlier removal, feature selection, data splitting (80-20 rule was applied), and data scaling. Then, a number of methods such as linear regression (LR), multilayer perceptron (MLP), support vector machine (SVM), and committee machine intelligent system (CMIS) were used to link 1316 data samples assembled in this research work. Based on the obtained results, the CMIS model was proven to produce superior results compared to its counterparts such that the root mean squared rrror (RMSE) values for both training and testing data are 4.622 and 7.757, respectively. Based on the feature importance results, the presence of Ca2+ in the connate water, Na+ in the injected brine, core porosity, and total acid number of the crude oil are detected as the parameters with the highest impact on the RFf. The CMIS model proposed here can be applied with a high degree of confidence to predict the performance of LSWF in sandstone reservoirs. The database assembled for the purpose of this research work is so far the largest and most comprehensive of its kind, and it can be used to further delineate mechanisms behind LSWF and optimization of this EOR process in sandstone reservoirs.

Dataset Information

Percolation Characteristics and Fluid Movability Analysis in Tight Sandstone Oil Reservoirs.

Publications

Percolation Characteristics and Fluid Movability Analysis in Tight Sandstone Oil Reservoirs.

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