scholarly journals Logging Characteristics and Identification Methods of Low Resistivity Oil Layer: Upper Cretaceous of the Third Member of Qingshankou Formation, Daqingzijing Area, Songliao Basin, China

Geofluids ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Congjun Feng ◽  
Murray Gingras ◽  
Mengsi Sun ◽  
Bing Wang
Keyword(s):  
Water Saturation ◽  
Thick Layer ◽  
Water Layer ◽  
High Amplitude ◽  
Production Test ◽  
Tight Sandstone ◽  
Low Resistivity ◽  
The Third ◽  
Irreducible Water Saturation ◽  
Low Amplitude

This study focuses on low resistivity thick layer sandstone in the X~XII groups of the third member of Qingshankou Formation at Daqingzijing oilfield, along with comprehensive data of logging, core, oil test, and production test. Based on the current data, we characterized the logs of low resistivity thick-layer sandstone, quantitatively identified calcareous sandstone and low resistivity reservoir, predicted the reservoir thickness, and further explored the causes of low resistivity reservoir of the region. The resistivity of thick layer sandstone in the X~XII groups of Qingshankou Formation can be classified into low amplitude logfacies, middle amplitude logfacies, and sharp high amplitude logfacies. Sharp high amplitude logfacies sandstone is the tight sandstone of the calcareous cementation. Low amplitude logfacies sandstone is water layer. For the middle amplitude logfacies sandstone, water layer or oil-water layer can be identified with the identification standard. Low amplitude structure, high clay content, high irreducible water saturation, and high formation water salinity are attributed to the origin of low resistivity oil layer.

scholarly journals Using the Modified Resistivity–Porosity Cross Plot Method to Identify Formation Fluid Types in Tight Sandstone with Variable Water Salinity

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6335
Author(s):  
Yufei Yang ◽  
Kesai Li ◽  
Yuanyuan Wang ◽  
Hucheng Deng ◽  
Jianhua He ◽  
...  
Keyword(s):  
Water Saturation ◽  
Ordos Basin ◽  
Water Layer ◽  
Water Salinity ◽  
Water Type ◽  
Formation Water ◽  
Tight Sandstone ◽  
Fluid Identification ◽  
Low Resistivity ◽  
Formation Water Salinity

It is generally difficult to identify fluid types in low-porosity and low-permeability reservoirs, and the Chang 8 Member in the Ordos Basin is a typical example. In the Chang 8 Member of Yanchang Formation in the Zhenyuan area of Ordos Basin, affected by lithology and physical properties, the resistivity of the oil layer and water layer are close, which brings great difficulties to fluid type identification. In this paper, we first analyzed the geological and petrophysical characteristics of the study area, and found that high clay content is one of the reasons for the low-resistivity oil pay layer. Then, the formation water types and characteristics of formation water salinity were studied. The water type was mainly CaCl2, and formation water salinity had a great difference in the study area ranging from 7510 ppm to 72,590 ppm, which is the main cause of the low-resistivity oil pay layer. According to the reservoir fluid logging response characteristics, the water saturation boundary of the oil layer, oil–water layer and water layer were determined to be 30%, 65% and 80%, respectively. We modified the traditional resistivity–porosity cross plot method based on Archie’s equations, and established three basic plates with variable formation water salinity, respectively. The above method was used to identify the fluid types of the reservoirs, and the application results indicate that the modified method agrees well with the perforation test data, which can effectively improve the accuracy of fluid identification. The accuracy of the plate is 88.1%. The findings of this study can help for a better understanding of fluid identification and formation evaluation.

scholarly journals Permeability Prediction of Tight Sandstone Reservoirs Using Improved BP Neural Network

2015 ◽  
Vol 8 (1) ◽  
pp. 288-292 ◽  
Author(s):  
Peng Zhu ◽  
Chengyan Lin ◽  
Peng Wu ◽  
Ruifeng Fan ◽  
Hualian Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Water Saturation ◽  
Controlling Factors ◽  
Convergence Speed ◽  
Oil Field ◽  
Tight Sandstone ◽  
Irreducible Water Saturation

By analyzing the permeability controlling factors of tight sandstone reservoir in Wuhaozhuang Oil Field, the permeability is considered to be mainly controlled by porosity, clay content, irreducible water saturation and diagenetic coefficient. Because the conventional BP algorithm has its drawbacks such as slow convergence speed and easy falling into the local minimum value, an improved three-layer feed-forward BP neural network model is built by MATLAB neural network toolbox to predict permeability according to the four permeability controlling factors, while studying samples of model are selected based on the representative core analysis data. The simulation based on improved neural network model shows that the improved model has a faster convergence speed and better accuracy. The consistency between model prediction value and lab test value is good and the mean squared error is less. Therefore, the new model can meet the needs of the development geology research of oil field better in the future.

Applications of Conventional Logs in Low Resistivity Contrast Tight Gas Reservoirs Identification

2013 ◽  
Vol 734-737 ◽  
pp. 41-44
Author(s):  
Xiao Peng Liu ◽  
Xiao Xin Hu ◽  
Xiao Ling Zhang ◽  
Rui Xu ◽  
Ling Ling Zhi
Keyword(s):  
Water Saturation ◽  
Total Porosity ◽  
Ratio Method ◽  
Tight Gas ◽  
Low Resistivity ◽  
Irreducible Water Saturation ◽  
The Difference ◽  
Tight Gas Formation ◽  
Conventional Logs ◽  
Gas Bearing

It’s a great challenge in identifying gas bearing formation from conventional logs in tight gas sandstones due to the low resistivity contrast caused by high irreducible water saturation. Based on the difference of the principles of three kinds of porosity logs (density, neutron and acoustic logs), three porosities difference method, three porosities ratio method, correlation of neutron and density logs and the overlap method of water-filled porosity and total porosity are introduced to identify tight gas bearing reservoirs. In gas bearing formations, the difference of three porosities is higher than 0.0, the ratio of three porosities is higher than 1.0, the correlation between density and neutron logs is negative, and the water filled porosities are lower than total porosities. On the contrary, in water saturated formations, the difference of three porosities is lower than 0.0, the ratio of three porosities is lower than 1.0, the correlation between density and neutron logs is positive, and the water filled porosities are overlapped with total porosities. Considering the complexity of in-suit formation, when the proposed identification criterion are mainly meet, the pore fluid should be determined, field examples show that the proposed techniques are applicable in tight gas formation identification.

scholarly journals ANALISIS PETROFISIKA DAN PENYEBAB LOW RESISTIVITY RESERVOIR ZONE BERDASARKAN DATA LOG, SEM, XRD DAN PETROGRAFI PADA LAPANGAN X SUMATERA SELATAN

2020 ◽  
Vol 4 (2) ◽  
pp. 31-46
Author(s):  
Rita Aprilia ◽  
Ordas Dewanto ◽  
Karyanto Karyanto ◽  
Aldis Ramadhan
Keyword(s):  
Oil And Gas ◽  
Water Saturation ◽  
Water Reservoir ◽  
Water Layer ◽  
Research Area ◽  
Low Resistivity ◽  
Hydrocarbon Reservoir ◽  
Gas Layer ◽  
Data Log ◽  
Resistivity Log

Hydrocarbon reservoir zone located on Low Resistivity is a typical and hidden oil and gas layer which always wrong in assessing as a water layer due to the complex geological origin and resistivity log limitation in identifying hydrocarbon. Presence of shale in a reservoir will decreasing resistivity value and increasing saturation value, so it can cause the results of the analysis to be pessimistic in the identification of hydrocarbons. In that case need to do analysis to core data on research area in order to know the cause of Low Resistivity on reservoir zone that having a probability of hydrocarbon content. Reservoir zone that has low resistivity value is at depth 1572-1577 mD. In this zone, it has a low resistivity value around 2.7- 4.4 ohm-m, with water saturation value around 47%-74% which causes on Low Resistivity reservoir zone to be between hydrocarbons and water reservoir zone. Then, on this research, Low Resistivity is also caused by Lamination Clay of shale type presence which consists of several types of Clay which can cause reservoir zone is at low resistivity value. This Clay type consist of Kaolite 20%, Illite 4%, and Chlorite 4% minerals as well as the presence of other minerals as proponent of low resistivity that is Quartz 60%, Plagioclase 9% and Calcite 3% as conductive minerals.

scholarly journals Calculation Model of Relative Permeability in Tight Sandstone Gas Reservoir with Stress Sensitivity

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jin Yan ◽  
Rongchen Zheng ◽  
Peng Chen ◽  
Shuping Wang ◽  
Yunqing Shi
Keyword(s):  
Relative Permeability ◽  
Pore Radius ◽  
Water Saturation ◽  
Stress Sensitivity ◽  
Tight Sandstone ◽  
Gas Reservoir ◽  
Two Phase ◽  
Permeability Model ◽  
Irreducible Water Saturation ◽  
Tight Gas Reservoir

During the development of tight gas reservoir, the irreducible water saturation, rock permeability, and relative permeability change with formation pressure, which has a significant impact on well production. Based on capillary bundle model and fractal theory, the irreducible water saturation model, permeability model, and relative permeability model are constructed considering the influence of water film and stress sensitivity at the same time. The accuracy of this model is verified by results of nuclear magnetic experiment and comparison with previous models. The effects of some factors on irreducible water saturation, permeability, and relative permeability curves are discussed. The results show that the stress sensitivity will obviously reduce the formation permeability and increase the irreducible water saturation, and the existence of water film will reduce the permeability of gas phase. The increase of elastic modulus weakens the stress sensitivity of reservoir. The irreducible water saturation increases, and the relative permeability curve changes little with the increase of effective stress. When the minimum pore radius is constant, the ratio of maximum pore radius to minimum pore radius increases, the permeability increases, the irreducible water saturation decreases obviously, and the two-phase flow interval of relative permeability curve increases. When the displacement pressure increases, the irreducible water saturation decreases, and the interval of two-phase flow increases. These models can calculate the irreducible water saturation, permeability and relative permeability curves under any pressure in the development of tight gas reservoir. The findings of this study can help for better understanding of the productivity evaluation and performance prediction of tight sandstone gas reservoirs.

Applicability of Classical Permeability Estimation Models Based on NMR Logging in Tight Sandstones

2013 ◽  
Vol 772 ◽  
pp. 814-818 ◽  
Author(s):  
Deng Feng Wei ◽  
Xiao Peng Liu ◽  
Xiao Xin Hu
Keyword(s):  
Water Saturation ◽  
Input Parameter ◽  
Data Sets ◽  
Tight Sandstone ◽  
Nmr Logging ◽  
Permeability Estimation ◽  
Single Function ◽  
Irreducible Water Saturation ◽  
Sdr Model ◽  
Sandstone Permeability

Permeability cannot be directly predicted from porosity by using a single function in tight sandstones reservoirs due to the extreme heterogeneity. The hydraulic flow unit (HFU) approach and classification scale method (CSM) are available in permeability prediction, while they are all significant time-consuming. In this paper, based on the analysis of the proposed data sets of lab NMR experimental measurements by Xiao et al. (2012; 2013), the applicability of the classical SDR (Schlumberger Doll Research) and Timur-Coates models, which are used to estimate permeability from NMR logging is analyzed. A field example shows that the Timur-Coates model is valuable in tight sandstone permeability estimation once the involved input parameter of irreducible water saturation (Swi) can be accurately calculated without acquiring T2cutoff. While the SDR model is not available because the effects of hydrocarbon to NMR spectra cannot be removed.

Performance Evaluation of Gas Production With Consideration of Dynamic Capillary Pressure in Tight Sandstone Reservoirs

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Leng Tian ◽  
Bo Feng ◽  
Sixu Zheng ◽  
Daihong Gu ◽  
Xiaoxing Ren ◽  
...  
Keyword(s):  
Capillary Pressure ◽  
Production Rate ◽  
Water Saturation ◽  
Gas Production ◽  
Tight Sandstone ◽  
Mobile Water ◽  
Dynamic Capillary Pressure ◽  
Irreducible Water Saturation ◽  
Sandstone Reservoirs ◽  
Bottomhole Pressure

In this paper, a pragmatic and consistent framework has been developed and validated to accurately predict reservoir performance in tight sandstone reservoirs by coupling the dynamic capillary pressure with gas production models. Theoretically, the concept of pseudo-mobile water saturation, which is defined as the water saturation between irreducible water saturation and cutoff water saturation, is proposed to couple dynamic capillary pressure and stress-induced permeability to form an equation matrix that is solved by using the implicit pressure and explicit saturations (IMPES) method. Compared with the conventional methods, the newly developed model predicts a lower cumulative gas production but a higher reservoir pressure and a higher flowing bottomhole pressure at the end of the stable period. Physically, a higher gas production rate induces a greater dynamic capillary pressure, while both cutoff water saturation and stress-induced permeability impose a similar impact on the dynamic capillary pressure, though the corresponding degrees are varied. Due to the dynamic capillary pressure, pseudo-mobile water saturation controlled by the displacement pressure drop also affects the gas production. The higher the gas production rate is, the greater the effect of dynamic capillary pressure on the cumulative gas production, formation pressure, and flowing bottomhole pressure will be. By taking the dynamic capillary pressure into account, it can be more accurate to predict the performance of a gas reservoir and the length of stable production period, allowing for making more reasonable development schemes and thus improving the gas recovery in a tight sandstone reservoir.

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