A Case Study To Evaluate Shale Gas Performance Models With Actual Well Production Data

Author(s):  
Hong Yuan ◽  
Mofazzal H. Bhuiyan ◽  
Jiafu Xu
2001 ◽  
Vol 41 (1) ◽  
pp. 679
Author(s):  
S. Reymond ◽  
E. Matthews ◽  
B. Sissons

This case study illustrates how 3D generalised inversion of seismic facies for reservoir parameters can be successfully applied to image and laterally predict reservoir parameters in laterally discontinuous turbiditic depositional environment where hydrocarbon pools are located in complex combined stratigraphic-structural traps. Such conditions mean that structural mapping is inadequate to define traps and to estimate reserves in place. Conventional seismic amplitude analysis has been used to aid definition but was not sufficient to guarantee presence of economic hydrocarbons in potential reservoir pools. The Ngatoro Field in Taranaki, New Zealand has been producing for nine years. Currently the field is producing 1,000 bopd from seven wells and at three surface locations down from a peak of over 1,500 bopd. The field production stations have been analysed using new techniques in 3D seismic imaging to locate bypassed oils and identify undrained pools. To define the objectives of the study, three questions were asked:Can we image reservoir pools in a complex stratigraphic and structural environment where conventional grid-based interpretation is not applicable due to lack of lateral continuity in reservoir properties?Can we distinguish fluids within each reservoir pools?Can we extrapolate reservoir parameters observed at drilled locations to the entire field using 3D seismic data to build a 3D reservoir model?Using new 3D seismic attributes such as bright spot indicators, attenuation and edge enhancing volumes coupled with 6 AVO (Amplitude Versus Offset) volumes integrated into a single class cube of reservoir properties, made the mapping of reservoir pools possible over the entire data set. In addition, four fluid types, as observed in more than 20 reservoir pools were validated by final inverted results to allow lateral prediction of fluid contents in un-drilled reservoir targets. Well production data and 3D seismic inverted volume were later integrated to build a 3D reservoir model to support updated volumetrics reserves computation and to define additional targets for exploration drilling, additional well planning and to define a water injection plan for pools already in production.


2020 ◽  
Vol 39 (6) ◽  
pp. 8823-8830
Author(s):  
Jiafeng Li ◽  
Hui Hu ◽  
Xiang Li ◽  
Qian Jin ◽  
Tianhao Huang

Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods


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