Reservoir Modelling PDF - 4th Year

Reservoir Modelling 4th Year 5- The Modelling Workflow: There are five major steps in the modelling workflow as follows (Fig.4): 1- Data collection, analysis and loading. ▲ Collect the input data ▲ Undertake qualitative...

Reservoir Modelling 4th Year 5- The Modelling Workflow: There are five major steps in the modelling workflow as follows (Fig.4): 1- Data collection, analysis and loading. ▲ Collect the input data ▲ Undertake qualitative and quantitative sedimentological and stratigraphic studies. 2- Build the reservoir framework. ▲ Structural Model ▲ Stratigraphic Model ▲ Geocellular Model 3- Build the facies model. ▲ Facies Model 4- Build the property model. ▲Property Model ▲Volumetric Model. 5- Build the dynamic simulation model. ▲ Simulation Model ▲ Uncertainty Model Fig.4- Reservoir modelling workflow elements 8 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year 6- Basic Geological Elements in Modelling (Fig. 5): ▲ Zone: Geological unit bounded by horizons ▲ Horizons: are specific layers within the geological strata that are characterized by particular properties, such as lithology, age, or fossil content. the main types are  Interpreted Horizons: Seismic interpretation  Calculated Horizons: Zonation and stratigraphic modelling computed using thickness information ▲ Surface: Surfaces in geological models refer to the boundaries or interfaces between different geological units or zones. These surfaces can represent various geological features, such as: Stratigraphic Surfaces, Unconformities, and Fault Surfaces. ▲ Well: Described by a trajectory (path) and associated logs, in addition to a well history. The intersection between wells and horizons (etc) are called markers or picks. Note: Property Surfaces, horizons and zones may have multiple associated properties, e.g. a porosity or a fault multiplier. Fig.5- Basic Geological Elements in Modelling 9 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year 6- Properties of Reservoirs: 6-1 Static Properties: Static reservoir properties are those rock properties that normally do not change during the life of a field. They are the result of primary depositional processes coupled with postdepositional burial, diagenesis, and tectonics. Static properties include:  Stratigraphy  Geometry  Size  Lithologies  Structure Framework,  Initial Porosity and Permeability  Temperature 6-2 Dynamic Properties: Dynamic reservoir properties are those that do change significantly during the life of a field. These properties can play a key role in production optimization and monitoring the EOR operation or hydraulic fracturing. Dynamic properties include:  Fluid saturations  Fluid contacts  Production and fluid-flow rates  Pressure  Fluid compositions, including gas-to-oil ratio (GOR) and water-to-oil ratio (WOR)  Acoustic (seismic) properties (Seismic attributes are dynamic, because fluid type and content change during oil and gas production) 10 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year 7- Key Elements of Reservoir Modelling: Reservoir modeling is a process of integrating geological, geophysical, and petrophysical data into a 3D description of a reservoir. It requires input data to geometrically define the reservoir and condition its property modeling, and it yields a 3D model that describes the main characteristics of the reservoir regarding its rock properties, volumetric, and fluid flow (Fig-6). Fig.6: Key elements of reservoir modeling 7-1 Specific Reasons for Constructing 3D Models: 1. There is a need for reliable estimates of the original volume of hydrocarbon in the reservoir. 2. Well locations must be selected to be economically optimal and robust with respect to uncertainty in the reservoir description. 3. There is often a need to reconcile an abundance of soft data with a limited amount of hard well data. 4. Major decisions must be made in the presence of significant uncertainty. 11 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year 8. Data in Reservoir Modelling: 8.1 Input Data: Oil and gas reservoir modelling involves two broad classes of data:  Static (for example, core, well logs, and seismic interpretation)  Dynamic (pressure and fluid production observed at wells). Integration of dynamic data together with static data enhances the quality of the reservoir models generated and provides the reservoir engineers with a better basis for reservoir simulation and management. The importance of data integration are: 1- Improved accuracy in predictions 2- Enhanced risk assessment 3- Better decision-making in resource management Notes: Data required to define the geometry of a reservoir model include a polygon that delineates the lateral extension of the model and the top and base surfaces of the reservoir, which define the vertical positions and thickness of the model. In addition, intermediate surfaces may be required to define the internal stratigraphic architecture of the model. The bounding and intermediate surfaces can be from seismic interpretations and/or mapped from the formation markers at wells, typically derived from stratigraphic correlations. 12 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year When faults are present and influence the fluid flow, they are inputs for defining a faulted model framework. Faults are usually obtained from the interpretation of seismic data. For petrophysical properties model data, are generally obtained from petrophysical analysis of well logs and cores. Dynamic data that change with time can also be used for reservoir modeling. These include production data measured at wells, such as pressures and liquid and gas production rates. 8.2 Data Collection and Management: Data management is probably the most important part of any modelling project. The quality of input data is the essential element of a modelling project; if there are any inconsistencies in the input data, they will show up in the end results and at every intermediate modelling steps. The primary data types used for reservoir modelling are as follows: Well Data: direct sampling from cores, indirect measurements from well logs (with high-resolution indication of facies and fluids), and modern image logs (information on sedimentary structures and faults). Seismic Data: provide valuable information on large-scale reservoir geometry. Dynamic Data: from well tests, historical production 13 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year 8.2.1 Well Data: The well data are generally represents a very small investigation volume for the reservoir that is to be modelled, but it is also the ‘hardest’ data available to the project team. A- Core Data: Available from a limited number of wells. Core may be sampled by relatively small core plugs, or entire sections of core may be measured for whole core data. Core derived data give us information detailed about Sedimentology, petrography, environment of deposition, Porosity, permeability, grain density, fluids shows and Petrophysical core-to-log calibration Fig-7: Core Sample B- Wellbore Path: Wellbore path data are computed from suitable corrected direction survey data and are stored in the database. Wellbore path is the trajectory of a directionally drilled well in three dimensions. Data is the emphasis on the following (Fig-8): 1- Calculate directional coordinates. 2- Calculate the true vertical depth (TVD) and Total depth (TD). 3- Identify Kick-off point (KOP) (is the depth at which the well is first deviated from the vertical) and End of Build-up point (EOB) (Landing point). 14 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year Note: (Directional drilling is the methodology for directing a wellbore along a predetermined trajectory to a target. Vertical wells are usually defined as wells with an inclination within 5°. Wells with a section having an inclination greater than 85° for a significant distance are called Horizontal wells). Fig-8: Well Path C- Wireline Logs and MWD/LWD Logs: Provide a continuous high-resolution record of accurate information on stratigraphic surfaces, measurements of petrophysical properties such as facies types, φ, and, perhaps, k measurements The graphical logs containing all the primary measurements in a wellbore. As a minimum, it will contain well header data, primary well logs. The Composite log should integrate the geological columnar section with selected petrophysical logs 15 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year i.e. a lithology indicating log, a porosity log and a resistivity log. Geological zones lithology core intervals. Logs should be pre-processed for modelling purposes and a set of curves assembled either in the project data store or in a separate petrophysical database (Fig- 9). These data will form the ‘basic input data’ for reservoir modelling. Fig-9: Well Logs D- Computer-Processed Interpretation (CPI) Logs: 16 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4th Year Well logs data processing and interpretation are complex processes and they involve mathematical, statistical, and numerical techniques. Well-log data evaluation and analysis can be carried out manually and/or by employing a computer. The primary source for reservoir property data is the petrophysical interpretation of porosity and water saturation (Fig-10). Fig-10: CPI Logs 17 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4 th Year Seismic data: Seismic data is one of the most important sources of data used in reservoir modeling. It provides information about the subsurface structure, including the depth, thickness, and location of reservoirs. Seismic data is obtained by sending sound waves into the ground and measuring the time it takes for the waves to bounce back. Seismic exploration can be divided into three main stages: data acquisition, processing and interpretation. The seismic sweep is the set of sound frequencies directed into the subsurface (Fig. 11). Seismic reflections indicate potential rock transitions, and these properties of the reflections provide information on the relative nature of the transition. Fig. 11: Seismic Reflection Method 18 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4 th Year Seismic data represents the primary source for horizon and fault input to the reservoir model (Fig.12). Seismic data provide information on fault locations, large- scale reservoir geometry, and large-scale variations in facies proportions. Fig. 12: Seismic Section A- Horizon: Interpreted seismic horizon time data are imported from the database to the project data store. Depth-converted versions of the horizons should also be stored. A Seismic Horizon is defined as a set of free points/lines in time that are effectively continuous over large parts of the area of interest. (The contact between two bodies of rock having different seismic velocity, density, porosity, fluid content or all of those). B- Faults Polygons and Sticks: Fault Polygons are line data representing the hanging wall and footwall for each horizon (Fig-13 and 14). 19 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4 th Year Fault Sticks: set of data that represent the fault plane (fault surface) (Fig-13 and 14). Input Fault Plain #2 Horizon Input Input #4 #1 Horizon Input #3 Fig-13: Fault input data Fig-14: Fault walls and plane 20 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4 th Year C- Velocity Model: The velocity model is generally stored in the project data store either as a function, a grid or as a cube. The data can be loaded into the project if depth conversion is to be carried out as part of the modelling exercise. Alternatively, depth-converted surfaces and fault information are provided. Fig-15 D- Seismic Data Volume: A number of different seismic volumes may be loaded depending on the different processing results; different products may aid structural interpretation or enhance attribute analysis. Capture the structural and stratigraphic framework of a field in 3D dimensions. 21 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4 th Year Fig-16 3D seismic Data 8.2.3 Dynamic Data: A dynamic reservoir model is a representation of the changes in fluid flow in the reservoir model that need to be validated with reservoir performance data-pressure changes, production and injection rates. A- Fluid Data Oil and gas fluid data are required to evaluate the properties of produced fluids at reservoir conditions, in production tubing, in process facilities and in pipeline transportation. The key PVT (pressure–volume–temperature) properties to be determined for a reservoir fluid include the following: Original reservoir fluid composition Saturation pressure at reservoir temperature Oil and gas densities and viscosities. 22 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering  Reservoir Modelling 4 th Year Gas solubility in reservoir oil Liquid content of a reservoir gas Shrinkage (volume) factors (Bo, Bg, Bw) of oil, gas and water from reservoir to surface conditions. Compositional variation with depth B- Well Test Data Well test data can be used to determine effective permeability. It is divided into the following types: Transient well test (DST) raw data: rates and pressures. Well tests: perforation intervals and main interpretation data, Permeability thickness, boundaries. Production log interpretations: oil, gas and water rates in the well, plus pressure distribution. 8.2.4 Important Specialist Data Special Core Analysis: Special core analysis data should be collected for defining petrophysical interpretation parameters and for dynamic measurements. Routinely collected data include the Archie parameters a, m and n, capillary pressure, wettability and relative permeability. These values are collected and used in the petrophysical assessment for the reservoir and later in dynamic modelling. 23 Dr. Maha M. Al-Dabagh Petroleum and Mining Engineering