Three-dimensional geological modeling of reservoirs is an essential tool to predict reservoir performance and improve the understanding of reservoir uniqueness in Es1 formation. The paper focuses on the use of petrel software to build three-dimensional reservoir geological model which characterizes and assesses block Nv32 that located in the west of the Shenvsi oilfield in the south of Cangzhou city, Hebei province of China, and has an oil-bearing area of 1.4 km 2. This study is depending on integration data from well logs of 22 wells which provided from geology, geophysics, and petrophysics to identify and provide precise depict of the subsurface internal structure and the reservoir heterogeneity. Input data was used to build the structural model, sedimentary facies model, petrophysical properties (porosity, permeability, saturation, and N/G model, and finally to determine the reservoir volume. The lithological facies were simulated using the assigned value method. Moreover, Petrophysical properties (Porosity, permeability, oil saturation and net to gross) were constructed for each zone using the Sequential Gaussian Simulation method to guide the distribution of petrophysical properties of Es1 formation, block Nv32. Statistical analysis of the porosity, permeability, oil saturation and N/G model present that the porosity occurrence distribution is mainly concern between 0.2% - 36.39% of block Nv32 with an average porosity value of 17.5%, permeability between 0.017 mD to 974.8 mD, having an average permeability of 59.44 mD, oil saturation between 0.00 to 0.95 having an average value of 0.22, and N/G is mainly concentrated between 0.01 to 1.00 within an average value of 0.61. This research has indicated the reliability of the three-dimensional model technique as a suitable tool to provide a sufficient understanding of petrophysical distribution. The south-western and north-western indicate that oilfield is very promising an exploratory well should be drilled to find out the thickness and size of the reservoir.
When the oil has been discovered in a field, many studies will be required to evaluate and comprehend the reservoir heterogeneity, define the extent of the reservoir in the three-dimensional, evaluating the fluid volumetric in the reservoir and identify the suitable method to increase the reservoir fluid recovery. Generally, reservoir characteristics such as lithofacies heterogeneities, porosity, and permeability spatial variation control the reservoir performance, and development plans [
Block Nv32 is located in the west of the Shenvsi oilfield (Dagan oilfield) in the south of Cangzhou City, Hebei province and its structure locate in between Cangxian and Kongdian structures. Due to the complex structure and fault development of the Shenvsi Oilfield, there are many blocks in the oil field. Moreover, block Nv32 mainly contains sandstone and carbonate rocks, sandstone with lithic argillaceous sandstone, feldspathic lithic sandstone, and a small amount of mixed sandstone. The structural area of the sand-oil top structure is 2.0 km2, the structural width is 100 m, the proven oil-bearing area is 1.4 km2, and the petroleum geological reserves are 225 × 104 t.
The data used for this research were obtained from block Nv32 in China. These data include structural maps, fault lines, and well logs. Data were checked and organized properly, and then imported into Petrel software to build the 3D reservoir model. The workflow design used for the study and wide range of functional tools in the petrel software includes 3D visualization, well correlation, 3D mapping, and 3D grid design for geology simulation, well log upscaling, petrophysical modeling, data analysis, and volume calculation.
Data preparation is the foremost stage for constructing a reservoir static model. Geomap3.6 and Petrel software are the chiefly software to construct this model. Based on Petrel’s demand and area characteristics of Es1 formation, block Nv32. Three types of data were required to construct this reservoir static model which can be concluded as: well path data, structure data, and property data. Well path data to describe the pathway of wells across, while structure data is used to create a 3D grid, which includes individual layers data and fault data, on the other hand; Property data is used to generate property model by applying numerical analysis calculation to the data by property definition [
Wells correlation has been performed to provide clear depict about the reservoir geological characteristic such as thickness change within Es1 formation units block Nv32, and the change of petrophysical properties such as a change in (Porosity, permeability, oil saturation, and N/G) of different units in Es1 formation. In accordance with data input into Petrel software, the correlation section for twenty-two well was performed. The sequence was subdivided into a lithological unit namely Shale, Sandstone, Limestone according to the sand characteristics of Es1 formation, Nv32 block. The correlating process of Es1 formation wells was made by using different logs such as Spontaneous potential (SP), Caliper (CAL) and Acoustic impedance (AC) logs to perform the well to well correlation. After data were inputted into Petrel software, the correlation section of Es1 formation was performed.
Structural modeling in Petrel is subdivided into three operations which can be included as follows: Fault modeling, Pillar gridding, and vertical layering. All the mentioned processes were performed sequentially to form a single data model [
The fault model was the primary step for constructing a structure model with petrel workflow tools. Es1 formation mainly consists of fifteen faults. Fault type in bock Nv32 is normal and reverse fault. This fault model has used the fault polygon which Petrel software provides to each type of vertical fault, diagonal fault, curve fault, and various geometry structure fault according to the fault polygon. The initial surface was established by applying fault polygon with various stratification planes, then fault section was corrected by adjusting the fault section, uses breakpoint data obtained by single well correlation, correct the position and shape of fault revision fault and shape, make it convenient and anastomosing.
Identify the thickness and the directions of layers among the horizons of this 3D grid was the final step to construct the structure framework. Moreover, Modern geology required an accurate illustration of layered volumes. Recently, the three-dimensional geological model is the most effective method for constructing the geological model at depth [
Facies modeling is discrete throughout the model grid. Facies model of Es1 Formation, block Nv32 has constructed the base on the outcome result of the microfacies interpretation of sedimentary environments as obtained from logs. The Es1 formation primarily consists of three types of lithology which are shale, limestone, and sandstone with a proportion of 32.42%, 29.49%, and 38.09% respectively. However, limestone is the predominated reservoir rock in block Nv32. The assigned value method was applied to simulate the sand bodies in Es1 formation. Figures 7-10 illustrate the facies model for each zone of Es1 formation, block Nv32.
Petrophysical property modeling is known as the process of distributing reservoir properties into the geological grid. This is performed individually for each reservoir zone of the geological grid [
Evaluate oil capacity in the oil reservoir is achieved by determining its porosity. The porosity model of Es1 formation was built based on the outcome result that has been determined from porosity which was obtained from the petrophysical interpretation of block Nv32 wells. In this model, the porosity model was constructed for each unit of Es1 formation, block Nv32. The arithmetic average method was applied to scale up the well logs. Sequential Gaussian Simulation method was used to distribute the porosity in the model. The porosity occurrence distribution is a concern between 0.2% - 36.39% of Es1 formation, block Nv32 with an average porosity value of 17.5%.
| Type of Data | Continuous (%) |
|---|---|
| Min | 0.2 |
| Max | 36.39 |
| Mean | 17.5 |
| Std.dev. | 8.54 |
Permeability is an essential parameter in the reservoir rock. Its measure of the ease with which a fluid flows through the connecting pore space of the reservoir rock. The reservoir rock permeability is a vital property to determine the orientation movement and flow rate of the reservoir fluid in the formation. In this model, the permeability model was based on the permeability log generated [
The saturation distribution model is known as the percentage between oil, water, and gas in the reservoir pore space. Saturation is an essential tool to identify a high prospective water area [
Net to Gross ratio is used to eliminate non-productive reservoir rock unit if exist. Moreover, limestone is the predominant reservoir rock of Es1 formation. Thus, Net to gross was set to unity for the volume calculation. The arithmetic average method was applied to scale up the well logs. Moreover, the Sequential Gaussian Simulation method was used to build the Net to Gross model of Es1 formation, block Nv32. Net to Gross model shows that the N/G of Es1 formation is primarily concentrated between 0.01 and 1.00 within an average value of 0.61.
| Type of Data | Continuous (%) |
|---|---|
| Min | 0.00 |
| Max | 1.00 |
| Mean | 0.613 |
| Std. Dev. | 0.449 |
Estimate the quantity of hydrocarbon in the reservoir is known as reservoir volumetric. Reservoir volumetric is an essential part of the geological model because it provides the basis for oilfield exploration and development. Furthermore, reservoir volumetric can examine the reliability of the model [
| Zones | Bulk Volume [×106 m3] | STOIIP (in oil) [×106 sm3] |
|---|---|---|
| Es1 × 1 | 43.894771 | 0.554368 |
| Es1 × 2 | 36.879991 | 4.7069397 |
| Es1 × 3 | 29.936135 | 4.7828403 |
| Es1 × 4 | 27.843010 | 10.0377143 |
| Case | 138.553907 | 20.0819 |
The overall values such as porosity and permeability indicate that Es1 formation, block Nv32 is a good and promising oilfield, because of its good porosity and permeability values.
1) The structural model has been completed for Es1 formation, block Nv32. This model describes the structure trap characteristic, identify the distribution, geometry structure, reservoir attitude, and development of faults and fractures of Es1 formation, block Nv32.
2) Horizons were constructed for Es1 formation, block Nv32, and they are divided into 4 zones namely as Es1 × 1, Es1 × 2, Es1 × 3, and Es1 × 4. Based on the facies, petrophysical properties, layers were built for each zone. Es1 × 1, Es1 × 2 zones were divided into 11 layers. However, Es1 × 3 and Es1 × 4 were divided into10layers, and this was based on the thickness and petrophysical properties.
3) Facies modeling for block Nv32 was built using the assigned value method. This model shows that Es1 formation consists of three types of lithology which are shale, limestone, and sandstone with a proportion of 32.42%, 29.49%, and 38.09% respectively. However, limestone is the predominated rock in this reservoir.
4) The petrophysical model (porosity, permeability, oil saturation, and Net to Gross) of Es1 formation was built based on their values using the Sequential Gaussian Simulation method as a statistical method. Es1 × 3 and Es1 × 4 are the highest petrophysical properties in terms of porosity, permeability.
My deepest thanks and gratitude go to my parents, brothers, and professor Guan Zhenliang for their high support and motivation. I would like to convey my special thanks to Dr. Atif Zafar for his sincere advice and continuous support as well as constructive comments which helped me to think critically.
The authors declare no conflicts of interest regarding the publication of this paper.
Rassas, A.A., Ren, S., Sun, R., Zafar, A., Moharam, S., Guan, Z., Ahmed, A. and Alomaisi, M. (2020) Application of 3D Reservoir Geological Model on Es1 Formation, Block Nv32, Shenvsi Oilfield, China. Open Journal of Yangtze Gas and Oil, 5, 54-72. https://doi.org/10.4236/ojogas.2020.52006