Permeability Determination from Stoneley Waves in the Ara Group

Qobi, Latifa; Kuijper, Andre; Tang, X.; Strauss, Jonathan B.; Munkholm, Mette

doi:10.2523/63140-ms

Cited by 6 publications

(6 citation statements)

References 5 publications

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“…It has functional roles in permeability estimation (Qobi et al, 2001;Endo, 2006), wellbore stability calculations (Wendt et al, 2007), fracture evaluation (Brie et al, 1988), detecting thin gas beds (Tang and Patterson, 2001), and formation anisotropy estimation (Tang and Patterson, 2004). Due to the high cost of measuring, some wells may have no Vst data.…”

Section: Introductionmentioning

confidence: 98%

The Estimation of Stoneley Wave Velocity from Conventional Well Log Data: Using an Integration of Artificial Neural Networks

Asoodeh

Shadizadeh

Zargar

2015

Energy Sources, Part A: Recovery, Utilization, and Environmenta

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Stoneley wave velocity (Vst) is capable of providing accurate data for reservoir characterization objectives, such as permeability estimation, fracture evaluation, formation anisotropy identification, etc. At the first stage of this study, different types of artificial neural networks, including generalized regression neural network, radial basis neural network, and feed-forward backpropagation neural network were utilized to predict Vst from conventional well log data. Consequently, a generalized regression neural network was employed to combine results of mentioned artificial neural networks for overall estimation of Vst. This novel hybrid method can enhance the accuracy of final prediction through reaping the benefits of individual artificial neural networks. The proposed methodology, hybrid neural network, was applied in Asmari formation, which is the major carbonate reservoir rock of Iranian southern oil field. A group of 1,640 data points was used to establish the intelligent model, and a group of 800 data points was employed to assess the reliability of the constructed model. Results showed that integration of different artificial neural networks using generalized regression neural network can significantly improve the accuracy of final prediction.

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Section: Introductionmentioning

confidence: 98%

The Estimation of Stoneley Wave Velocity from Conventional Well Log Data: Using an Integration of Artificial Neural Networks

Asoodeh

Shadizadeh

Zargar

2015

Energy Sources, Part A: Recovery, Utilization, and Environmenta

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“…[1][2][3][4][5] In the horizontal fracture case, Stoneley waves are attenuated because of flow into the fracture and scattering by the fracture. 6 The fracture zone is traditionally modeled as a fluid-filled narrow parallel-plate channel in which fracture waves propagate.…”

Section: Introductionmentioning

confidence: 99%

Shock-induced wave propagation over porous and fractured borehole zones: Theory and experiments

Fan

Smeulders

2013

The Journal of the Acoustical Society of America

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Borehole waves are strongly affected by adjacent porous zones or by fractures intersecting the borehole. A theoretical description for both porous and fracture zones is possible based on the introduction of an effective borehole fluid bulk modulus, characterizing the wave attenuation via borehole wall impedance. This impedance can be calculated for both porous and fracture zones adjacent to the borehole, thus predicting borehole wave attenuation, transmission, and reflection over such zones. A shock tube setup generates borehole tube waves that are used for porous and fracture zone characterization. A PVC sample is used to introduce and vary fractures in a cylindrical sample. Shock wave experiments show that attenuation in boreholes adjacent to porous zones can be predicted by theory. The transmittivities of a borehole tube wave over 1 and 5 mm fractures are correctly predicted, thus showing the potential of borehole wave experiments for fracture detection and characterization.

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“…Also, determining the proper value of these crucial parameters exerts a profound impact on the primary and secondary oil recovery procedures, where the different layer permeabilities may lead to differential depletion. There are a wide variety of applied techniques to estimate the amount of permeability in the layered reservoirs in which the most important ones are core analysis, sidewall samples, wireline logging correlations, NMR logs, wireline formation testers, drill stem tests (DST), and production logging tools (Amir Shah et al 2017;Kading 1976;Qobi et al 2000;Quintero et al 1999;Saetrom et al 2016). …”

Section: Introductionmentioning

confidence: 99%

Integrated production logging tools approach for convenient experimental individual layer permeability measurements in a multi-layered fractured reservoir

Davarpanah

Mirshekari

Behbahani³

et al. 2018

J Petrol Explor Prod Technol

106

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Appropriate estimation of permeability is considered as one of the significant concerns of petroleum industries. Due to the growing demand for hydrocarbon fossil fuels in numerous industries, Petroleum Engineers always try to provide holistic and sustainable solutions to measure this parameter more accurately and to calculate the proper original oil in place (OOIP) and initial reserve. Hence, this accuracy estimation helps engineers whether the production and exploration operations are profitable or not and it might virtually eliminate the unnecessary expenditures. The term production logging tools (henceforth; PLT) involve a wide variety of measurement tools and many sensors. It, too, carries interpretation tools which evaluate the formation properties, in respect of the way PLTs would analyze the formation fluid movements inside and outside of the wellbore and subsequently estimate the production flow rate for each layer. On the other hand, it gives production and completion engineers the chance to investigate the appropriate efficiency of production and perforation processes to organize the remediation methodologies or preplan proper designing for modifying completion procedures which have based on the production logging tools interpretation. The purpose of this comprehensive research is to compare two different techniques (PLT and core analysis) of permeability measurement in a six-layered fractured reservoir and subsequently normalize each parameter to obtain the proper estimation. As a result, according to the evaluation of each technique, the amount of permeability in the layers 1, 2, 3, and 5 is relatively close to each other. Furthermore, regarding higher expenses of core analysis tests and the reliability of PLTs according to the results of this paper in the four out of six individual layers, Emeraude software by utilizing PLT interpretation could be a substitution and preferable methodology instead of core analysis measurements.

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Permeability Determination from Stoneley Waves in the Ara Group

Cited by 6 publications

References 5 publications

The Estimation of Stoneley Wave Velocity from Conventional Well Log Data: Using an Integration of Artificial Neural Networks

The Estimation of Stoneley Wave Velocity from Conventional Well Log Data: Using an Integration of Artificial Neural Networks

Shock-induced wave propagation over porous and fractured borehole zones: Theory and experiments

Integrated production logging tools approach for convenient experimental individual layer permeability measurements in a multi-layered fractured reservoir

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