Production Prediction Based on the Heterogeneity Analysis of the Tight Carbonate Reservoir in the Sichuan Basin, China

2015 ◽  
Author(s):  
B. Xie ◽  
Y. Wang ◽  
X. Zhou ◽  
Z. A. Zhao ◽  
X. Zhou ◽  
...  
Keyword(s):  
Sichuan Basin ◽  
Carbonate Reservoir ◽  
Tight Carbonate ◽  
The Sichuan Basin ◽  
Heterogeneity Analysis ◽  
Production Prediction

Prediction of deep-buried gas carbonate reservoir by combining prestack seismic-driven elastic properties with rock physics in Sichuan Basin, southwestern China

2014 ◽  
Vol 2 (4) ◽  
pp. T193-T204
Author(s):  
Jiqiang Ma ◽  
Jianhua Geng ◽  
Tonglou Guo
Keyword(s):  
Elastic Properties ◽  
Seismic Data ◽  
Sichuan Basin ◽  
Incident Angle ◽  
Rock Physics ◽  
Carbonate Reservoir ◽  
Southwestern China ◽  
Marine Carbonate ◽  
The Sichuan Basin ◽  
Elastic Impedance

The prediction of seismic reservoirs in marine carbonate areas in the Sichuan Basin, southwestern China, is very challenging because the target zone is deeply buried (more than 6 km), with multiphase tectonic movements, complex diagenesis, and low porosity, and the incident angle of the seismic data is finite. We developed reliable hydrocarbon indicators of a marine carbonate deposit based on prestack elastic impedance (EI) and well observations. Although the hydrocarbon indicators can be calculated from elastic parameters, the inversion for EI-driven elastic attributes is usually unstable. To constrain the inversion process, we discovered a new strategy to recover the elastic properties from EIs within a Bayesian framework (called Bayesian elastic parameter inversion from elastic impedance). We applied the strategy to a carbonate reef identified at the center of a study line based on the geologic context and the seismic reflection patterns. We then used rock-physics analyses to classify the lithologies and the reservoir at a well location. Rock-physics modeling quantified the hydrocarbon sensitivity of the elastic attributes. Fluid substitution was used to investigate the effects of pore fluids on the elastic properties. A comparison of two synthetic amplitude-versus-angle responses (for gas and brine saturation) with real seismic data showed that the reservoir was gas charged. Using well-based crossplot analyses, reliable direct hydrocarbon indicators can be constructed for a deeply buried gas reservoir and were effective for interpretation in an area of marine carbonates in the Sichuan Basin.

Fluid Identification Derived from Non-Electric Measurements and Reservoir Characterization of Tight Carbonate in Sichuan Basin, China

2021 ◽  
Author(s):  
Zuo AN Zhao ◽  
Yue Wang ◽  
Qiang Lai ◽  
Kai Xuan Li ◽  
Xian Ran Zhao ◽  
...  
Keyword(s):  
Sichuan Basin ◽  
Reservoir Characterization ◽  
Water Saturation ◽  
Carbonate Reservoirs ◽  
Free Fluid ◽  
Formation Water ◽  
Fluid Identification ◽  
Fluid Saturation ◽  
Tight Carbonate ◽  
The Sichuan Basin

Abstract Natural gas production in the Sichuan Basin reached 30 billion m3 in 2020, but the gap between this and the production goal of 50 billion m3 in 2025 requires further exploration. The complex mineralogy and low porosity in tight carbonate reservoirs lower the accuracy of formation water saturation calculation from Archie's equation, which brings uncertainties to the reservoir characterization. It is, therefore, necessary to incorporate other methods as supplements to methods based on resistivities. This paper outlines a method that incorporates wireline induced gamma spectroscopy, nuclear magnetic resonance (NMR), array dielectric, and borehole images. Spectroscopy is not only utilized to estimate the mineralogy of the reservoir, but it also provides non-electric measurements, such as chlorine concentration and thermal neutron capture cross-section (sigma). The amount of chlorine in the formation is proportional to the water volume in the reservoir, thus formation water saturation. Sigma is also an indicator of the formation water saturation. It enables formation water saturation calculation without resistivities. Case studies are presented from carbonate reservoirs in the Sichuan Basin, China. A robust and comprehensive petrophysical description of mineralogy, porosity, pore geometry, free fluid volume, rock type, and formation water saturation is presented. Calculation of formation water saturation from chlorine and sigma proves to be successful in both water-based mud and oil-based mud environments. The depth of investigation (DOI) of chlorine from spectroscopy is about 8 to 10 in. for 90% of the signal. The various DOI of different measurements must be considered when performing the fluid identification. Bound fluid saturation could reach more than 50% in tight carbonate reservoirs. Formation water saturation is not the only factor that determines the fluid type. Free fluid saturation from NMR must be incorporated. Finally, a robust methodology integrating formation water saturation derived from dielectric and spectroscopy, and free fluid saturation derived from NMR shows great advantage in fluid identification in tight carbonate reservoirs. This paper discusses a novel combination of wireline logging tools for the fluid identification of tight carbonate reservoir in Sichuan Basin. It lowers the uncertainty in the estimation of formation water saturation when application of resistivities is limited in oil-based mud environments. The gas zones identified by the new method have promising gas productions. The workflow can also be applied to other tight carbonate plays in China.

Vug and fracture characterization and gas production prediction by fractals: Carbonate reservoir of the Longwangmiao Formation in the Moxi-Gaoshiti area, Sichuan Basin

2020 ◽  
Vol 8 (3) ◽  
pp. SL159-SL171
Author(s):  
Chang Li ◽  
Liqiang Sima ◽  
Guoqiong Che ◽  
Wang Liang ◽  
Anjiang Shen ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Sichuan Basin ◽  
Fractal Dimensions ◽  
Gas Production ◽  
Carbonate Reservoir ◽  
Carbonate Reservoirs ◽  
Box Dimension ◽  
Longwangmiao Formation ◽  
Gas Production Prediction ◽  
Production Prediction

A comprehensive knowledge of the development and connectivity of fractures and vugs in carbonate reservoirs plays a key role in reservoir evaluation, ultimately affecting the gas prediction of this kind of heterogeneous reservoir. The carbonate reservoirs with fractures and vugs that are well developed in the Longwangmiao Formation, Sichuan Basin are selected as a research target, with the fractal dimension calculated from the full-bore formation microimager (FMI) image proposed to characterize the fractures and vugs. For this purpose, the multipoint statistics algorithm is first used to reconstruct a high-resolution FMI image of the full borehole wall. And then, the maximum class-variance method (the Otsu method) realizes the automatic threshold segmentation of the FMI image and acquisition of the binary image, which accurately characterizes the fractures and vugs. Finally, the fractal dimension is calculated by the box dimension algorithm, with its small value difference enlarged to obtain a new fractal parameter ([Formula: see text]). The fractal dimensions for four different kinds of reservoirs, including eight subdivided models of vugs and fractures, show that the fractal dimension can characterize the development and the connectivity of fractures and vugs comprehensively. That is, the more developed that the fractures and vugs are, the better the connectivity will be, and simultaneously the smaller that the values of the fractal dimensions are. The fractal dimension is first applied to the gas production prediction by means of constructing a new parameter ([Formula: see text]) defined as a multiple of the effective thickness ([Formula: see text]), porosity (Por), and fractal dimension ([Formula: see text]). The field examples illustrate that the fractal dimensions can effectively characterize the fractures and vugs in the heterogeneous carbonate reservoir and predict its gas production. In summary, the fractals expand the characterization method for the vugs and fractures in carbonate reservoirs and extend its new application in gas production prediction.

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