Selection of effective methods of increasing oil recovery in dealed fields based on retrospective analysis

The object of research is methods of increasing oil recovery in «old», depleted oilfields. One of the main tasks of the oil-extracting industry in any country in the world was and still is ensuring the project level of oil production at the maximum possible coefficient of its extraction from the subsoil. In this case it is extremely important to study and use technological methods and means of acquired experience in oilfield development. The paper considers the historical aspects of the development of stabilization and oil recovery methods from 1770s to the present day on the example of Ukrainian oilfields. In parallel with the history of the implementation of methods, their physical and technological content and conditions of application are discussed. Of all the methods used to increase the level of oil production, the most effective ones, which have found application at certain stages of the Ukrainian oilfields’ development, are considered. This is, first of all, a vacuum process, areal flooding, cyclic flooding, gas and water-gas repression, injection of surfactants, surfactant polymer-containing systems, polymer flooding, horizontal branched drilling. The methods development analysis is considered against the background of their geological and industrial acceptability and obtaining technical and economic effects. Based on the results of the study, a group of methods has been identified. These methods are advised to apply in geological and industrial conditions, similar to those described, which should ensure the expected efficiency. Undoubtedly, along with this, it is advisable to use the methods of mathematical modeling of oilfield development processes. Proposals are formulated on the conditions and principles of applying the methods under consideration in order to improve the systems for the development of oilfields. It has been established that the most acceptable methods of increasing oil recovery in depleted oilfields are the injection of surfactant solutions both independently and together with an aqueous solution of polyacrylamide, creation of gas-water repression and polymer flooding, in which preference is given to AN132SH and AN125SH reagents of FLOPAAM S series from SNF FlOERGEL.

Numerical Simulation of Temporal and Spatial Evolution of Stress Field in Unconsolidated Sandstone Oil Reservoir

Casing damage in the process of oilfield development is a serious problem, which is affected by geological structure, production technology and many other factors. To prevent casing damage, it is necessary to master the space-time evolution law of reservoir in-situ stress field, to provide support for casing damage prevention. Based on the perseage-stress coupling theory, taking the actual reservoir block as the research object, the change law of the in-situ stress field in unconsolidated sandstone reservoir is obtained through the fluid-solid coupling numerical simulation of the reservoir, and the internal correlation between the stress field and casing damage is analysed. The research results provide theoretical guidance for the formulation of casing damage prevention measures in the research block.

Comparison and adaptability evaluation of formation pressure calculation methods and computer simulation in Jingbian gas field

In the process of oilfield development, formation pressure is an essential parameter for evaluating oilfield development effect, calculating dynamic geological reserves, conducting daily dynamic analysis of oil and water Wells and predicting oilfield performance. The pressure recovery time of conventional gas well after shut-in is very long, and it is difficult to effectively carry out targeted implementation due to the influence of gas field external supply task. In this paper, based on the actual data of Jingbian gas field, through the comparison of several calculation methods of formation pressure, the best method to calculate formation pressure is comprehensively screened out. The results show that: ①For a single method, the accuracy of the method from high to low is the well head casing pressure conversion method, the pressure drop curve method, the binomial productivity equation method, and the quasi-steady state mathematical model method.②The absolute error of multi-method comprehensive calculation method is 0.9MPa, which is far less than the average absolute error directly calculated by one method. The multi-method comprehensive calculation method is reliable when applied to the formation pressure evaluation of typical gas Wells in Jingbian gas field, which lacks data.

Application of Micro-resistivity Scanning Imaging Logging Data in Reservoir Thickness Division

Reservoir parameter interpretation is one of the main contents of reservoir description, which affects the whole process of oilfield development. According to the characteristics of micro-resistivity scanning imaging logging, which can directly reflect the changes of lithology and physical properties of reservoirs, this paper compares the thickness and interbed division of reservoirs with conventional logging data, this paper finds out the shortcomings of the conventional logging data in the interpretation of thickness and the division of interlayers, and combines the core analysis data to examine the differences in the correlation on the coring wells, and obtains good results, it has laid the foundation for the establishment of new interpretation procedure.

Research Progress of Oilfield Development Index Prediction Based on Artificial Neural Networks

Accurately predicting oilfield development indicators (such as oil production, liquid production, current formation pressure, water cut, oil production rate, recovery rate, cost, profit, etc.) is to realize the rational and scientific development of oilfields, which is an important basis to ensure the stable production of the oilfield. Due to existing oilfield development index prediction methods being difficult to accurately reflect the complex nonlinear problem in the oil field development process, using the artificial neural network, which can predict the oilfield development index with the function of infinitely close to any non-linear function, will be the most ideal prediction method at present. This article summarizes four commonly used artificial neural networks: the BP neural network, the radial basis neural network, the generalized regression neural network, and the wavelet neural network, and mainly introduces their network structure, function types, calculation process and prediction results. Four kinds of artificial neural networks are optimized through various intelligent algorithms, and the principle and essence of optimization are analyzed. Furthermore, the advantages and disadvantages of the four artificial neural networks are summarized and compared. Finally, based on the application of artificial neural networks in other fields and on existing problems, a future development direction is proposed which can serve as a reference and guide for the research on accurate prediction of oilfield development indicators.