scholarly journals Single Well Productivity Prediction Model for Fracture-Vuggy Reservoir Based on Selected Seismic Attributes

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4134
Author(s):  
Shuozhen Wang ◽  
Shuoliang Wang ◽  
Chunlei Yu ◽  
Haifeng Liu
Keyword(s):  
Pearson Correlation ◽  
Prediction Method ◽  
Seismic Attributes ◽  
Flow Coefficient ◽  
New Method ◽  
Fluid Distribution ◽  
Well Productivity ◽  
Medium Model ◽  
Single Well ◽  
Productivity Prediction

Single well productivity is an important index of oilfield production planning and economic evaluation. Due to fracture-vuggy reservoirs being characteristically strongly heterogeneous and having complex fluid distribution, the commonly used single well productivity prediction methods for fracture-vuggy reservoirs have many problems, such as difficulty in obtaining reservoir parameters and producing large errors in the forecast values of single well productivity. In this paper, based on the triple medium model, the Laplace transform and Duhamel principle are used to obtain the productivity equation of a single well in a fracture-vuggy reservoir. Secondly, the seismic attributes affecting the productivity of a single well are selected using the Spearman and Pearson correlation index calculation method. Finally, the selected seismic attributes are introduced into the productivity equation of the triple medium model through the interporosity flow coefficient and the elastic storativity ratio, and the undetermined coefficients under different karst backgrounds are determined using multiple nonlinear regression. From these, a new method for predicting single well productivity of fracture-vuggy reservoir is established. In order to verify the feasibility of the new method, based on the actual production data of a fracture-vuggy reservoir in Xinjiang, the new single well productivity prediction method is used to predict the productivity of 134 oil wells. The results show that the new productivity prediction method not only reduces calculation workload, but also improves the accuracy of productivity prediction, which contributes to a good foundation for future oilfield development.

Gas-Water Flow Behaviour During Mutual Displacement in Porous Media

2017 ◽  
Vol 10 (1) ◽  
pp. 13-22
Author(s):  
Renyi Cao ◽  
Junjie Xu ◽  
Xiaoping Yang ◽  
Renkai Jiang ◽  
Changchao Chen
Keyword(s):  
Porous Media ◽  
Relative Permeability ◽  
Gas Storage ◽  
Fluid Distribution ◽  
Water Displacement ◽  
Phase Zone ◽  
Two Phase ◽  
Flow Process ◽  
Single Well ◽  
Mutual Displacement

During oilfield development, there exist multi-cycle gas–water mutual displacement processes. This means that a cycling process such as water driving gas–gas driving water–water driving gas is used for the operation of injection and production in a single well (such as foam huff and puff in single well or water-bearing gas storage). In this paper, by using core- and micro-pore scales model, we study the distribution of gas and water and the flow process of gas-water mutual displacement. We find that gas and water are easier to disperse in the porous media and do not flow in continuous gas and water phases. The Jamin effect of the gas or bubble becomes more severe and makes the flow mechanism of multi-cycle gas–water displacement different from the conventional water driving gas or gas driving water processes. Based on experiments of gas–water mutual displacement, the changing mechanism of gas–water displacement is determined. The results indicate that (1) after gas–water mutual displacement, the residual gas saturation of a gas–water coexistence zone becomes larger and the two-phase zone becomes narrower, (2) increasing the number of injection and production cycles causes the relative permeability of gas to increase and relative permeability for water to decrease, (3) it becomes easier for gas to intrude and the invaded water becomes more difficult to drive out and (4) the microcosmic fluid distribution of each stage have a great difference, which caused the two-phase region becomes narrower and effective volume of gas storage becomes narrower.

scholarly journals Weight Analysis of Influence Factors and Potential Evaluation Method for Chemical Combination Flooding

2018 ◽  
Vol 53 ◽  
pp. 01022
Author(s):  
LIU Zhaoxia ◽  
WANG Qiang ◽  
MA Desheng ◽  
Gaoming ◽  
LIU Wanlu
Keyword(s):  
Evaluation Method ◽  
Influence Factor ◽  
Comprehensive Evaluation ◽  
Influence Factors ◽  
Prediction Method ◽  
Weight Coefficient ◽  
New Method ◽  
Chemical Flooding ◽  
Evaluation Score ◽  
Chemical Combination

In this paper, the weight coefficient of influencing factors for chemical combination flooding is determined by using grey correlation theory. A calculation method for comprehensive evaluation score of chemical combination flooding is established. The influence factor grading and weight grading are combined in this method. By collecting and analysing chemical combination flooding field tests, a prediction method for chemical combination flooding is established by the exponential regression. It reflects the relationship between EOR of the chemical combination flooding and the comprehensive evaluation score. The new method is applied in 6 different reservoirs to evaluate the effect of chemical flooding. The new method determines the weight coefficient of influence factors for chemical combination flooding. It can quickly predict EOR factor of chemical flooding to provide a basis for chemical flooding planning in the field.

Real-Time Prediction Method for Performance Degradation Trend Based on Reliability Experimental Data

2013 ◽  
Vol 321-324 ◽  
pp. 757-761 ◽  
Author(s):  
Chen Liang Song ◽  
Zhen Liu ◽  
Bin Long ◽  
Cheng Lin Yang
Keyword(s):  
Experimental Data ◽  
Real Time ◽  
Field Data ◽  
Prediction Method ◽  
Field Method ◽  
Performance Degradation ◽  
New Method ◽  
Time Prediction ◽  
Prediction Result ◽  
The Relationship

According to the real-time prediction for performance degradation trend, the commonly used method is just based on field data. But this methods prediction result will not be so much ideal when the fitting of degradation trend of field data is not good. To solve the problem, the paper introduces a new method which is not only based on field method but also based on reliability experimental data coming from the history experiment. We use the relationship between the field data and reliability experimental data to get the result of the two kinds of data respectively and then get the weights according to the two prediction results. Finally, the final real-time prediction result for performance degradation tendency can obtain by allocating the weights to the two prediction results.

A New Method to Predict Gas Production Based on Fuzzy BP Artificial Neural Network

2014 ◽  
Vol 1044-1045 ◽  
pp. 688-691
Author(s):  
Ran Zhang ◽  
Jun Zhou ◽  
Cheng Yong Li
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Gas Production ◽  
Gas Well ◽  
Well Productivity ◽  
Qualitative Factors ◽  
Productivity Prediction

BP neural network has been successfully used in the gas well productivity prediction, but as a result of neural network is sensitive to the number of input parameters, we had to ignore some factors that is less important to the gas well productivity. In addition, the existing various productivity prediction method cannot consider the influence of some important qualitative factors. This article integrated the advantages of fuzzy comprehensive evaluation and BP neural network, fuzzy comprehensive evaluation method is used to construct the BP neural network's input matrix, and BP neural network learning function is used to solve the connection weights, so as to achieve the aim of predicting gas production. This method not only can consider as many factors influence on gas well production, ut also can consider qualitative factors, so the forecast results of the new model are more realistically close to the actual production situation of reservoirs.

Prediction of the Effect of Impeller Trimming on the Hydraulic Performance of Low Specific-Speed Centrifugal Pumps

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
D. G. J. Detert Oude Weme ◽  
M. S. van der Schoot ◽  
N. P. Kruyt ◽  
E. J. J. van der Zijden
Keyword(s):  
Flow Field ◽  
Prediction Method ◽  
Hydraulic Performance ◽  
New Method ◽  
Prediction Methods ◽  
Centrifugal Pumps ◽  
Flow Rates ◽  
Pump Head ◽  
Low Specific Speed ◽  
Specific Speed

The effect of trimming of radial impellers on the hydraulic performance of low specific-speed centrifugal pumps is studied. Prediction methods from literature, together with a new prediction method that is based on the simplified description of the flow field in the impeller, are used to quantify the effect of trimming on the hydraulic performance. The predictions by these methods are compared to measured effects of trimming on the hydraulic performance for an extensive set of pumps for flow rates in the range of 80% to 110% of the best efficiency point. Of the considered methods, the new prediction method is more accurate (even for a large impeller trim of 12%) than the considered methods from literature. The new method generally overestimates the reduction in the pump head after trimming, and hence results less often in impeller trims that are too large when the method is used to determine the amount of trimming that is necessary in order to attain a specified head.

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