Automatic Well Selection Method for Acid-Fracturing in Kazakhstan R Oilfield Carbonate Reservoir

He Wen Zhang; Hong Lan Zou; Yun Hong Ding

doi:10.4028/www.scientific.net/AMM.333-335.1446

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 333-335Automatic Well Selection Method for...

Automatic Well Selection Method for Acid-Fracturing in Kazakhstan R Oilfield Carbonate Reservoir

Abstract:

In order to increase success rate and production of acid-fractured wells in Kazakhstan R oilfield, this paper compared various well-selection mathematic methods. Artificial neural network was chosen as a better way to predict production rate and finally choose target wells. Besides, some problems of this algorithm, such as normalization of input data, infection of order, were optimized to make it possible to be realized. With realistic data, sample database was set up and predictable model was also gotten. Its proven that the predicted results are very close to realistic data. Also, we analyzed the sensitivity of different parameters, and some useful conclusions were given: acid-fracturing is more effective for low and medium permeability reservoirs; if each layer could be treated separately, wells with large permeability differential will be better choice for acid-fracturing; bottomhole pressure is not the higher the better.

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Periodical:

Applied Mechanics and Materials (Volumes 333-335)

Pages:

1446-1451

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.333-335.1446

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Online since:

July 2013

Authors:

He Wen Zhang, Hong Lan Zou, Yun Hong Ding

Keywords:

Acid-Fracture, Artificial Neural Network (ANN), Carbonate Reservoir, Well Selection

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References

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