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Improving the accuracy of geological models and seismic sedimentology using sedimentary forward modeling

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Reservoir description based on geostatistics requires cross well constraints (such as high-quality seismic data) to predict the quality of cross well reservoirs that conform to geological laws. However, the seismic data resolution of multiple basins or reservoirs is not sufficient to identify the distribution of different types of sand bodies. This article proposes a new method to improve the accuracy of reservoir description: reservoir modeling under the constraints of sedimentary process models and sedimentary microfacies. Using a process based forward modeling method for strata, the modeling of the Dongying Formation reservoir in Block X of Dawa Oilfield is constrained. We divide reservoir modeling into three different steps. Firstly, a sand ratio model that can reflect the macroscopic distribution of the reservoir is obtained through sedimentary simulation, The model should be able to reflect the sedimentary law of the plane and the vertical sedimentary structure on seismic data. Secondly, using the sand ratio obtained from sedimentary simulation as a constraint condition, a high-precision sand ratio prediction model is established using the sequential Gaussian simulation method based on the sand ratio data from the well. Thirdly, based on the characteristics of the sand ratio, the sand ratio model is transformed into a sedimentary microfacies model. Under the facies controlled modeling method, the porosity Modeling permeability and oil saturation. The high-resolution reservoir model indicates that the porosity, permeability, and oil saturation of distributary channels are greater than 20%, 10 × 10−3 μm2, and 50%, respectively, far higher than other types of sedimentary microfacies. The results indicate that compared with other types of sedimentation, distributary channels have better physical properties and more oil and gas accumulation in the front of the fan delta, making them the most favorable oil and gas development zone in the study area.
Title: Improving the accuracy of geological models and seismic sedimentology using sedimentary forward modeling
Description:
Reservoir description based on geostatistics requires cross well constraints (such as high-quality seismic data) to predict the quality of cross well reservoirs that conform to geological laws.
However, the seismic data resolution of multiple basins or reservoirs is not sufficient to identify the distribution of different types of sand bodies.
This article proposes a new method to improve the accuracy of reservoir description: reservoir modeling under the constraints of sedimentary process models and sedimentary microfacies.
Using a process based forward modeling method for strata, the modeling of the Dongying Formation reservoir in Block X of Dawa Oilfield is constrained.
We divide reservoir modeling into three different steps.
Firstly, a sand ratio model that can reflect the macroscopic distribution of the reservoir is obtained through sedimentary simulation, The model should be able to reflect the sedimentary law of the plane and the vertical sedimentary structure on seismic data.
Secondly, using the sand ratio obtained from sedimentary simulation as a constraint condition, a high-precision sand ratio prediction model is established using the sequential Gaussian simulation method based on the sand ratio data from the well.
Thirdly, based on the characteristics of the sand ratio, the sand ratio model is transformed into a sedimentary microfacies model.
Under the facies controlled modeling method, the porosity Modeling permeability and oil saturation.
The high-resolution reservoir model indicates that the porosity, permeability, and oil saturation of distributary channels are greater than 20%, 10 × 10−3 μm2, and 50%, respectively, far higher than other types of sedimentary microfacies.
The results indicate that compared with other types of sedimentation, distributary channels have better physical properties and more oil and gas accumulation in the front of the fan delta, making them the most favorable oil and gas development zone in the study area.

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