A deep-learning-based prediction method of the estimated ultimate recovery(EUR)of shale gas wells

The estimated ultimate recovery(EUR)of shale gas wells is influenced by many factors,and the accurate prediction still faces certain challenges.As an artificial intelligence algorithm,deep learning yields notable advantages in nonlinear regression.Therefore,it is feasible to predict the EUR of shale gas wells based on a deep-learning algorithm.In this paper,according to geological evaluation data,hydraulic fracturing data,production data and EUR evaluation results of 282 wells in the WY shale gas field,a deep-learning-based algorithm for EUR evaluation of shale gas wells was designed and realized.First,the existing EUR evaluation methods of shale gas wells and the deep feedforward neural network algorithm was systematically analyzed.Second,the technical process of a deep-learning-based algorithm for EUR prediction of shale gas wells was designed.Finally,by means of real data obtained from the WY shale gas field,several different cases were applied to testify the validity and accuracy of the proposed approach.The results show that the EUR prediction with high accuracy.In addition,the results are affected by the variety and number of input parameters,the network structure and hyperparameters.The proposed approach can be extended to other shale fields using the similar technic process.

Multifunctional anti-wax coatings for paraffin control in oil pipelines

Paraffin deposition is a severe global problem during crude oil production and transportation.To inhibit the formation of paraffin deposits,the commonly used methods are mechanical cleaning,coating the pipe to provide a smooth surface and reduce paraffin adhesion,electric heating,ultrasonic and microbial treatments,the use of paraffin inhibitors,etc.Pipeline coatings not only have the advantages of simple preparation and broad applications,but also maintain a long-term efficient and stable effect.In recent years,important progress has been made in research on pipe coatings for mitigating and preventing paraffin deposition.Several novel superhydrophilic organogel coatings with low surface energy were successfully prepared by bionic design.This paper reviews different types of coatings for inhibiting wax deposition in the petroleum industry.The research prospects and directions of this rapidly developing field are also briefly discussed.

Valuable Data Extraction for Resistivity Imaging Logging Interpretation

Imaging logging has become a popular means of well logging because it can visually represent the lithologic and structural characteristics of strata.The manual interpretation of imaging logging is affected by the limitations of the naked eye and experiential factors.As a result,manual interpretation accuracy is low.Therefore,it is highly useful to develop effective automatic imaging logging interpretation by machine learning.Resistivity imaging logging is the most widely used technology for imaging logging.In this paper,we propose an automatic extraction procedure for the geological features in resistivity imaging logging images.This procedure is based on machine learning and achieves good results in practical applications.Acknowledging that the existence of valueless data significantly affects the recognition effect,we propose three strategies for the identification of valueless data based on binary classification.We compare the effect of the three strategies both on an experimental dataset and in a production environment,and find that the merging method is the best performing of the three strategies.It effectively identifies the valueless data in the well logging images,thus significantly improving the automatic recognition effect of geological features in resistivity logging images.