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Jidong oilfield belongs to complex fault block reservoir, and the development has now entered into high water-cut stage. when using Well pattern encryption technology to stabilize production, it is necessary to study the feasibility of Well pattern encryption to ensure a better economic benefit. In this paper, we use theoretical analysis method, consider the influence of oil price on the calculation, improve the economic limit Well pattern density calculation formula, calculate the economic limit Well pattern density under different recovery rates, make recovery rate prediction for different Well pattern density scenarios by combining with Sherkachov's formula, and use the curve intersection method to determine the Well pattern density at the break-even point, so as to determine the economic feasibility of Well pattern encryption. The example calculations show that the use of well network encryption alone does not meet the development requirements of the Liu 90 South block and has no significant economic benefits, so a combination of two-three methods is needed to further improve the recovery rate. Numerical simulation prediction results show that the two-three combination method can improve the recovery rate by 14.54%, accumulate 28.88×104t of oil increase and increase revenue by 678,245,000 yuan.

Surfactant flooding is a common technique in tertiary oil recovery. However, due to the high temperature of some reservoirs and the strong heterogeneity caused by their own geological conditions, the use of common surfactants in high-temperature reservoirs is limited. Temperature - resistant surfactants can reduce interfacial tension, improve conformance and increase oil washing efficiency In this paper, a temperature-resistant nano-type surface active JCN-001 was developed in the laboratory. By testing its particle size distribution, the experimental results can determine that the average particle size range of the system is 34.29nm, so that it can play a better role in low permeability reservoir recovery. Due to its unique nano properties, JCN at 0.2% concentration can still maintain a good effect at about 110, and the oil/water interfacial tension can reach 10-4nm/m, and can also reach ultra-low interfacial tension at high temperature, and the higher the temperature, the more significant the effect According to the changes of surface tension and oil-water interfacial tension, the critical micelle concentration was determined to be about 0.2%. The static adsorption experiments and dynamic adsorption experiments were carried out. The results show that the temperature resistant nano-surfactants have strong adsorption resistance and can effectively reduce the consumption of surfactants on rocks.

Carbon dioxide (CO2) gas is one of the main greenhouse gases. The detection of CO2 gas content is of great significance to the study of the greenhouse effect. The CO2 detection system based on the principle of tunable diode laser absorption spectroscopy (TDLAS) was demonstrated. A distributed feedback (DFB) laser with a central wavelength of 1580 nm was used as the laser source, multipass gas cell (MPGC) was used as gas cell, and indium gallium arsenic (IGA) photodetector was used to complete photoelectric conversion, and the original extracted second harmonic signal was smooth and denoised by wavelet transform. The signal‐to‐noise ratio (SNR) of the wavelet‐filtered spectrum improved from 6.88 to 13.87 dB, an improvement of 2.02 times. Principal component analysis was used to reduce the complexity of the data by compressing the spectrum from 800 dimensions to 2 dimensions. For the concentration inversion, the back‐propagation deep neural network (BP‐DNN) model was used to perform standard gas concentration step experiments and compared with the back‐propagation neural network (BPNN). The experimental results show that the BP‐DNN inversion of CO2 concentration has improved computational accuracy and the root mean square error (RMSE) is 3.55 times lower than that of the traditional BPNN, showing favorable application prospects. [ABSTRACT FROM AUTHOR]

A distribution feedback laser sensor for high precision and high sensitivity detection of the hydrogen sulfide in associated gas from oil fields is developed in this paper. Tunable diode laser absorption spectroscopy and wavelength modulation spectroscopy and were utilized for the H2S concentration detection in the oilfield. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm is used to remove the noise from the spectral signal. Particle swarm optimization‐least squares support vector machine (PSO‐LSSVM) model is applied for concentration prediction. The root mean square error of long‐term stability is 0.323. Allan–Werle deviation analysis shows that the theoretical limit of detection is 71 parts per billion while the optimal integration time reaches 96 s. The sensor is of great significance for real‐time detection of hydrogen sulfide concentration in associated gas in oil fields. [ABSTRACT FROM AUTHOR]