Porosity and permeability are the reservoirs important physical properties. Other features include the drainage area, which is the areal extent of the reservoir determined from the geological information about that region. Second, the expected ultimate recovery is the amount of oil or gas that companies can economically recover from a reservoir. The third property is the formation compressibility, which is the change in the vent volume per unit of change in pressure. Four, the gas saturation is the fraction of the pore space filled with gas. Note that, if the gas reservoir is a section of a gas cap in a full oil reservoir, space may contain gas, oil and, water. The fifth property of a deposit is its initial pressure, which is the pressure of fluids within the pores of the reservoir. Six, the oil saturation is the fraction of the pore space occupied by oil. Finally, the lake temperature is the temperature of the formation.
Pressure, volume, and temperature (PVT) investigation is the establishment of the features and behavior of reservoir fluid under different conditions, for example, pressure, volumes, and temperature. Mainly, the primary objectives of the analysis are to estimate the amount of crude oil and gas, to calculate the flow properties of the reservoir fluids, to optimize the liquid recovery, and to avail details about pressure maintenance. Petroleum service providers conduct PVT analysis to avail accurate data that aids in making qualitative engineering decisions. The report has made it easy to comprehend the complex behavior of reservoir fluids. Apparently, engineers collect surface gas and oil samples from the well sites to conduct the study. Then, the researchers use an ISCS integrated instrument called a capillary viscometer system to determine the properties.
Applications of PVT Analysis
Apparently, the PVT analysis provides results for reservoir engineering purposes and supports the design and optimization of procedures and equipment. Notably, it aids the engineers to maximize the hydrocarbon recovery at a low cost. Therefore, using the ideal gas law, PV=nRT, one can calculate the PVT analysis. Additionally, the estimated values can also help in establishing the reservoir pressure and the compressibility feature of the fluid.
Type of Tests Performed in PVT Analysis
Engineers use various experimental methods to perform PVT analysis. First, they conduct the multistage separator test on oil samples mainly to determine a basis for converting differential liberation information from a residual oil to a stock-tank oil basis. Typically, engineers conduct several separator tests to establish the separator conditions that maximize stock-tank oil production. It involves two or three stages of separation, with the last phase being at atmospheric pressure and near-ambient temperature of 15 to 250C. Second, engineers use the constant composition expansion (CCE) experiment to discern the bubble point pressure, the undersaturated oil density, the isothermal oil compressibility, and the two-phase volumetric behavior at pressures below the bubble point. Third, the differential liberation expansion (DLE) test is useful in the approximation of the depletion process of an oil reservoir, and therefore, provides adequate PVT data for calculating reservoir performance. Finally, the constant volume depletion (CVD) experiment provides volumetric and compositional statistics for gas condensate that a deposit produced by pressure reduction.
Compositional Analysis of a Separator Liquid
Compositional analysis refers to the measurement of the distribution of hydrocarbons and other elements present in oil and gas samples. Reservoir engineers use modern chromatography methods to analyze samples to establish the breakdown of the elements in the sample. Compositional analysis is useful in assessing the quality of samples and aids to discern reservoir continuity and investigate leakage. The liquid analysis is between C1 to C35 plus C36.
Material Balance Equation (MBE)
Principle of MBE
Material balance analysis is an interpretation technique that reservoir engineers use to determine original fluids-in-place (OFIP) based on production and static pressure data. The general material balance equation links the first oil, gas, and water in the reservoir to the production volumes and current load conditions or fluid properties. The equation assumes that the reservoir has the same pressure and fluid properties at any location. However, this assumption is only reasonable when the engineer obtains quality production and static pressure measurements. One can describe the general form of the material balance equation, as net withdrawal equals the enlargement of the hydrocarbon fluids in the system plus increasing water influx as shown below.
MBE Application or Uses
The material balance is an essential concept in reservoir engineering because it is a performance-based technique used to determine the original volume of hydrocarbons found in a deposit, which comprises many wells. Additionally, the procedure of matching pressure-based depletion trends between wells provides the reservoir engineer with the ability to develop a performance-based view of the linked pore volume in the deposit.
Drive indices for oil reservoirs designate the relative magnitude of the different energy sources acting in the reservoir. An easy illustration of a drive index is the ratio of a particular expansion term to the net withdrawal, normally referred to as the hydrocarbon voidage. The drive indices are cumulative and change with the production of the reservoir. The primary drive indices include the depletion drive index, the water drive index, the segregation or gas cap drive index, and the connate water compressibility index . Note that, if the drive indices do not sum to unity or close to one, then the engineer has not obtained the correct solution to the material balance.
Depletion Drive Index (DDI) =( NEo)/F
Water Drive Index (WDI) = (WeBw - WpBw)/F
Segregation Drive Index (SDI) = (NmEg(Boi/Bgi))/F
Connate Compressibility Index (CDI) = (N(1+m) EfwBoi)/F
Diagnostics - Dake and Campbell
Engineers use Dake and Campbell plots as diagnostic techniques to identify the reservoir type based on the signature of production and pressure behavior . One bases the plots on the assumption of a volumetric reservoir and uses the deviation from this practice to discern the reservoir type. In the Dake plot, the engineer uses the simplest oil case of solution gas or the depletion drive to determine the axes of the plot.
On the other hand, the Campbell plot is similar to the Dake plot although it incorporates a gas cap when required. In the Campbell plot, one plots the withdrawal against the pullout over total expansion, while neglecting the water influx term. Note that, if the reservoir lacks a water flow, the data will plot as a horizontal line. If there is water flow, the withdrawal over total expansion term will increase proportionally to the water influx over complete development. See below the Campbell plot.
Production and Development History of a Reservoir
Following the uncertainty in the earth model properties, forecasts based upon it will be uncertain too. Therefore, to reduce this risk, reservoir engineers use any historical production data that exists in the reservoir simulation. This is to determine whether the fields history is reproducible by the simulator based on earth model features. Accordingly, this step is known as history matching. Once a company matches the reservoir simulation to its production history, then it can forecast future production and plan the development of the reservoir. Below is the flow diagram that shows the production and development process of an oil reservoir from exploration, to well development, to production, and to reservoir abandonment.
Decline Curve Analysis
The decline curve analysis (DCA) is a graphical process used for analyzing diminishing production rates and predicting the future performance of oil and gas wells. It is important to note that, oil and gas production rates reduce as a function of time, loss of reservoir pressure, or varying relative volumes of the produced fluids . Fitting a line through the performance history and assuming this similar trend will continue in the future forms the basis of this concept. Nevertheless, in the absence of stabilized production patterns, the reservoir engineers cannot expect the technique to avail reliable results. The underlying assumption of the decline curve analysis is that the causes that earlier controlled the pattern of a curve will continue to monitor the trend in the future in a similar manner.
Scholars base this technique on empirical observation of production decline. Apparently, there are three types of declines observed, namely, the exponential decrease, the hyperbolic decline, and the harmonic fall. A reservoir engineer needs to be aware of several things while performing the DCA analysis. They include the most representative period in the past that will also represent the future, the declining trend during that time, the start rate of forecast, and the constraints under which he or she requires to make the projection needs. Additionally, it is paramount at this stage to determine the type of decline.
Well Performance Analysis
The well performance analysis is a combination of various elements of oil or gas well used to predict the flow rates and to optimize different aspects in the system. The first component, the reservoir part, represents the movement via the porous rock and given the increase in the concept of inflow performance relationship (IPR). The IPR of a well links the gross liquid well-bore-production rate to the bottom-hole-production pressure. The second component is the vertical component. The vertical multi-phase influx in the tubing string describes this part. Notably, this vertical multi-phase flow comprises two categories, namely, the multi-phase through vertical pipes and the multi-phase flow through annuli. The multi-phase through vertical pipes predicts flow pattern, liquid holdup and pressure drop in wells and pipelines . Therefore, it is crucial for the determination of pressure drop in both vertical pipes and horizontal flow lines. On the other hand, the multi-phase through annuli predicts the mixture behavior for upward two-phase flow in the concentric annulus. It consists of a procedure for flow pattern prediction and a group of models for calculating pressure decline in each of the selected flow patterns.
The third component is the horizontal component, which is the best method to calculate the pressure drops through the flow line. Finally, the choke component calculates the pressure loss using two types of flow, namely, the critical and subcritical flows. Apparently, in the critical flow, the flow rate is independent of the downstream pressure when the upstream pressure is constant. However, to analyze the total production system, it is paramount to develop a computer program that links the inflow performance relationship, the vertical multiphase flow computations, the choke performance calculations, and the flow line calculations. Note that, the software programs each component of the production system individually and then links them to establish the pressure losses in every element and the excellent production system design for particular reservoir conditions and surface facility constraints.
Well Test Analysis
A well test analysis is a valuable tool that reservoir engineers use to understand the well and reservoir performance. Engineers conduct well tests at all stages of the life of oil and gas fields. In other words, they test these wells from exploration, development, production, and injection...
If you are the original author of this essay and no longer wish to have it published on the ProEssays website, please click below to request its removal:
- Public Transport System Development
- The Impact of Technology and Marketing on Designers
- Essay on Different Types of Cars
- Review of Tesla Solar City Products, Services, and the Market Served. Company Report Example.
- Green Roof and Thermal Performance: Articles Review Example
- Technology Essay Example: Solar Panels
- Security and Privacy in the Internet of Things