A Hybrid Model for Selecting Horizontal Candidate Wells for Re-Fracturing of Tight Oil Reservoirs—A Case Study in the Baikouquan Formation, North Mahu Oil Field, Western China

2019 ◽  
Author(s):  
Zhaozhong Yang ◽  
Rui He ◽  
Jianlin Chen ◽  
Xiaogang Li ◽  
Bin Xie ◽  
...  
Keyword(s):  
Hybrid Model ◽  
Oil Field ◽  
Oil Reservoirs ◽  
Western China ◽  
Tight Oil ◽  
Tight Oil Reservoirs

scholarly journals Methods for estimating petrophysical parameters from well logs in tight oil reservoirs: a case study

2016 ◽  
Vol 13 (1) ◽  
pp. 78-85 ◽  
Author(s):  
Peiqiang Zhao ◽  
Wen Zhuang ◽  
Zhongchun Sun ◽  
Zhenlin Wang ◽  
Xingping Luo ◽  
...  
Keyword(s):  
Oil Reservoirs ◽  
Well Logs ◽  
Tight Oil ◽  
Petrophysical Parameters ◽  
Tight Oil Reservoirs

An enhanced accuracy method to determine oil saturation by carbon/oxygen logging in tight reservoirs

Geophysics ◽  
2021 ◽  
pp. 1-47
Author(s):  
Feng Zhag ◽  
Jilin Fan ◽  
Fei Qiu ◽  
Bing Xie ◽  
Xianghui Li ◽  
...  
Keyword(s):  
Energy Spectrum ◽  
Oil Field ◽  
Oil Reservoirs ◽  
Tight Oil ◽  
Denoising Method ◽  
Oil Saturation ◽  
Permeability Characteristics ◽  
Statistical Fluctuations ◽  
Tight Reservoirs ◽  
Tight Oil Reservoirs

The low porosity and permeability characteristics of tight oil reservoirs have brought challenges to monitoring oil saturation recently. Although carbon/oxygen logging is effective for oil saturation evaluation, the statistical fluctuations of the measured energy spectrum in tight reservoirs make it impossible to distinguish the different signals between oil and water. Thus, Noise Adjusted Singular Value Decomposition (NASVD) is applied to denoise the raw energy spectrum and evaluate the oil saturation quantitatively. The energy spectrum matrix, which is composed of the energy spectrum of the measurement point and its adjacent depth points, is decomposed and reconstructed to remove non-informative signals and improve the signal-to-noise ratio (SNR) of the raw energy spectrum. The parameter K evaluates the smoothness of the logging curves, reflecting the influence of the number of energy spectra and singular values on NASVD. Meanwhile, the NASVD, Savitzky-Golay (S-G) filtering and depth averaging methods are compared for calculating the accuracy of C/O, Si/Ca and oil saturation with the Monte Carlo method, indicating that NASVD is better than the other two methods for eliminating the statistical fluctuations of the raw energy spectrum. A simulation example indicates that NASVD can control the calculation errors of tight reservoir oil saturation to within 15%, which significantly improves the accuracy of the estimated oil saturation. An oil field example shows that the oil saturation interpretation result for tight reservoirs is in good agreement with the oil saturation from open hole log analysis, signifying that the NASVD energy spectrum denoising method can provide a quantitative estimate of oil saturation in tight oil reservoirs.

A New Productivity Prediction Hybrid Model for Multi-Fractured Horizontal Wells in Tight Oil Reservoirs

2021 ◽  
Author(s):  
Liang Tao ◽  
Jianchun Guo ◽  
Zhijun Li ◽  
Xuanyi Wang ◽  
Shubo Yang ◽  
...  
Keyword(s):  
Hybrid Model ◽  
Evaluation System ◽  
Horizontal Wells ◽  
Oil Reservoirs ◽  
Tight Oil ◽  
Factors Affecting ◽  
Tight Oil Reservoirs ◽  
Volume Fracturing ◽  
Fractured Horizontal Wells ◽  
Productivity Prediction

Abstract Single well productivity is an important index to evaluate the effect of volume fracturing. However, there are many factors affecting the productivity of Multi-fractured horizontal wells (MFHWs) in unconventional reservoirs and the relationship is complex, which makes productivity prediction very difficult. In this paper, taking the tight oil reservoir in Songliao Basin as the research object, a new mixed model of initial cumulative oil production of MFHWs was established, which can consider the geological factors and volume fracturing factors at the same time. Firstly, based on the big data, the multi-level evaluation system was established by using the analytic hierarchy process (AHP). Then, the weight factor was calculated to uncover key factors that dominate productivity of MFHWs. Finally, the fuzzy logic method was used to calculate the Euclidean distance and quantitatively predict the production of any horizontal wells. The simulation results shown that: the order of the main factors affecting production in the study area was horizontal section sandstone length, number of stages, formation pressure, proppant amount, net pay thickness, permeability, porosity, oil saturation, fracturing fluid volume. The hybrid model has been applied to the productivity prediction of 185 MFHWs in tight oil reservoirs in China, the prediction error was less than 5%. The new model can be used to predict production for MFHWs quickly and economically.

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