General Material Balance Equation 1.pptxssuser4978d4
油
The document discusses the derivation of the general material balance equation used to evaluate reservoir performance. It describes the assumptions made, including that the reservoir is treated as a single region with average pressure and temperature. The key terms in the equation are defined, such as initial oil/gas in place, cumulative production, and formation volume factors. An example calculation is shown applying the material balance equation to determine original oil/gas in place and quantify water influx from an aquifer.
This document discusses material balance equations used to relate fluid movement and production from a reservoir to the amount of fluids contained. It provides an equation that accounts for: 1) remaining oil, 2) free gas remaining, 3) change in gas cap volume, and 4) net water influx. The equation is based on conservation of mass as production causes pore volume contraction and fluid expansion/contraction. Applications of the material balance equation include calculating stock tank oil originally in place and gas originally in place.
prediction of original oil in place using material balance simulation. It's also useful for future reservoir performance and predict ultimate hydrocarbon recovery under various types of primary driving mechanisms.
This document provides an overview of reservoir fluid properties, including crude oil, water, and gas properties. It discusses key properties such as formation volume factors, viscosity, surface tension, and gas solubility. It summarizes various empirical correlations used to estimate these properties based on temperature, pressure, oil composition and other factors. The document is from a course on reservoir fluid properties and focuses on definitions and methods for calculating important PVT properties.
This document provides an overview of reservoir fluid properties, including crude oil, water, and gas properties. It discusses key crude oil properties such as formation volume factor, viscosity, and surface tension. It describes methods for calculating total formation volume factor, oil viscosity at different pressures, and surface tension. Water properties like water formation volume factor and viscosity are also covered. Empirical correlations are presented for estimating various fluid properties in the absence of experimental data.
Gas condensate reservoirs contain fluids that are intermediate between oil and gas. At initial reservoir conditions, the fluid is gas, but during production liquid forms due to pressure and temperature changes. Most gas condensate reservoirs exist at pressures between 3,000-6,000 psi and temperatures of 200-400属F. Efficient production requires either gas reinjection to maintain pressure above dew points or gas cycling to recover liquids and reinject dry gas. Pressure depletion alone is inefficient as it leaves liquids in place and lowers production rates over time.
This document discusses fluid flow and well productivity in reservoirs. It covers topics like different flow regimes based on boundaries, pressure behavior over time, productivity index concepts, and multiphase flow equations. The key points are:
1) Fluid flow in a well goes through different regimes as boundaries are encountered like infinite-acting, late transient, and pseudo-steady state where all boundaries are felt.
2) Productivity index (PI) is a measure of well productivity and is useful for comparing wells, estimating capacity, and identifying well problems.
3) Multiphase flow equations account for changing properties like relative permeability below the bubble point that impact productivity calculations.
Equations for Black Oil Properties from Flash, Differential an.docxYASHU40
油
Equations for Black Oil Properties from Flash, Differential and Separator Data
At bubble point (pb)
Let Bob = BoSb and Rsb = RsSb , taking the Separator Test values to be correct at the bubble point.
Bob = BoSb
Rsb = RsSb
Above bubble point (pb)
Use Flash Expansion Data (Vt/Vb)f and BoSb to obtain Bo above pb.
Bo = BoSb(Vt/Vb)f
Rs = RsSb = constant
Bo below bubble point (pb)
Use Differential Expansion Data (Bod/Bodb) and BoSb to obtain Bo below pb.
Bo = BoSb(Bod/Bodb)
Rs below bubble point (pb)
Where, RsSb = total gas in solution at bubble point (pb),
Rs = (Rsdb Rsd) = solution gas liberated while dropping pressure from pb to p in a differential test (this will be different than if done as a flash or separator test)
(BoSb/Bodb) is used to correct the differential-test-obtained Rs to what would have been obtained from a separator test for oil at pressure p.
Rs = RsSb (Rsdb Rsd)(Bosb/Bodb)
Oil Compressibility Equations
In terms of ordinary derivative [Eqn (1)]
Obtaining co from Flash Expansion Test data[Eqn (2)]
Integrated form of Eqn (2) [Eqn (3)]
Integrated form of Eqn (3) [Eqn (4)]
Test Data
Flash Data (p pb )
Differential Data (p pb )
Separator Test Data
p
(Vt/Vb)f
p
Bod = (Vo/VResid)d
Rsd
(Separator p = 200 psig)
5000
0.9639
pb = 2620
Bodb = 1.600
854.0
BoSb = 1.474 RVB/STB
4500
0.9703
2350
1.554
763.0
RsSb = 768 SCF/STB
4000
0.9771
2100
1.515
684.0
3500
0.9846
1850
1.479
612.0
3000
0.9929
1600
1.445
544.0
2900
0.9946
1350
1.412
479.0
2800
0.9964
1100
1.382
416.0
2700
0.9983
850
1.351
354.0
pb = 2620
1.000
600
1.320
292.0
350
1.283
223.0
159
1.244
157.0
0
1.075
0.0
0
1.000
In class problems:
1. At p = 2800 psig, determine: Bo, Rs.
2. At p = pb = 2620 psig, determine: Bob, Rsb.
3. At p = 1850 psig, determine: Bo, Rs.
Homework problems:
4. At p = 4500 psig, determine: Bo, Rs.
5. At p = pb = 2620 psig, determine: Bob, Rsb.
6. At p = 23500 psig, determine: Bo, Rs.
7. Determine the oil compressibility (co) between the bubble point pressure (pb = 2620) and p = 3500 psi.
Answers: 1. Bo = 1.4687 RVB/STB; Rs = 768 SCF/STB. 2,5. Bo = 1.474 RVB/STB; Rs = 768 SCF/STB.
3. Bo = 1.3625 RVB/STB; Rs = 545 SCF/STB. 4. Bo = 1.4302 RVB/STB; Rs = 768 SCF/STB.
6. Bo = 1.4316 RVB/STB; Rs = 684.17 SCF/STB 7. 0.0000176 1/psi
A. Informational Questions on Black Oil, Correlations and the Regression Process
1. What is a correlation? Give one example for gas and two for oil.
2. Regression is a process that involves several steps: (a) Determine which variables are significant;
(b) Determine a functional form; (b) Determine constants for that function to minimize error.
For black oil correlations, which three quantities appear in all correlations as the basic three variables?
Give three example functional forms:
3. Explain a black oil model for reservoir fluid properties. ...
This document provides an overview of key concepts in reservoir fluid properties including:
- Formation volume factors (Bo and Bt) which relate the volume of oil and gas in the reservoir to stock tank conditions.
- Methods for determining PVT properties like gas solubility and Bo/Bt through laboratory experiments as pressure changes.
- Key fluid properties like bubble point pressure, compressibility, and molecular weight that impact reservoir performance.
- Techniques for estimating fluid properties using correlations with parameters like boiling point and API gravity.
This document outlines topics covered in a reservoir engineering course, including reservoir fluid behaviors, properties of petroleum reservoirs, gas behavior, and properties of crude oil systems. It specifically discusses properties of interest like density, solution gas, bubble point pressure, formation volume factor, viscosity and more. It provides empirical correlations to estimate properties like gas solubility, bubble point pressure, and formation volume factor as a function of parameters like solubility, gas gravity, oil gravity and temperature. The document is focused on understanding physical properties of crude oil and gas reservoirs which is important for reservoir engineering applications and problem solving.
This document provides an overview of methods for calculating reservoir fluid properties, including crude oil and water properties. It discusses calculating the total formation volume factor (Bt) using correlations like Standing's and Glaso's. It also covers calculating crude oil viscosity, including dead-oil viscosity using Beal's correlation, saturated oil viscosity using Chew-Connally, and undersaturated oil viscosity using Vasquez-Beggs. The document provides equations and discusses experimental data ranges for various fluid property correlations.
This document describes procedures for analyzing reservoir fluid properties in the laboratory, including crude oil properties, water properties, and various laboratory tests. It discusses measuring the total formation volume factor, viscosity, surface tension, and other properties of crude oil and water. It also describes primary tests conducted on-site, routine laboratory tests like compositional analysis and constant-composition expansion, and special laboratory PVT tests. The constant-composition expansion test measures saturation pressure and compressibility by reducing pressure in a cell and measuring volume changes. The results are used to calculate fluid densities and compressibility coefficients above the saturation pressure.
Chapter 2 basic single phase-flow equationMichaelDang47
油
This document provides an overview of the derivation and development of the basic single-phase flow equations in reservoir simulation. It begins with the conservation principles of mass and momentum and the Darcy's law constitutive relationship. It then presents the continuity and single-phase flow equations for one-dimensional horizontal flow. Finally, it provides the 3D single-phase flow equation and a table of relevant quantities in the flow equations.
This document provides an overview of reservoir fluid properties including:
1. Crude oil properties such as density, gas solubility, bubble point pressure, formation volume factor, compressibility, and correlations to calculate these properties.
2. Water properties including water formation volume factor, viscosity, gas solubility in water, and water isothermal compressibility.
3. The total formation volume factor and viscosity of crude oil are also discussed along with definitions of dead-oil, saturated-oil, and undersaturated oil viscosities.
The document discusses laboratory analysis techniques for gas condensate systems, including recombination and analysis of separator samples, constant-composition expansion tests, and constant-volume depletion tests. It describes the procedures for these various laboratory experiments in detail, including determining fluid properties like compressibility factors and calculating quantities like retrograde liquid saturation and cumulative gas production. The goal is to better understand the pressure-volume-temperature behavior and compositional changes that occur during depletion of a gas condensate reservoir.
This document provides an overview of key reservoir fluid properties including methods for calculating z-factors, gas properties such as compressibility and viscosity, crude oil properties like density and solution gas, and empirical correlations for determining properties like gas solubility, bubble point pressure, and formation volume factors. The document discusses various correlations for estimating properties in the absence of laboratory measurements and defines important concepts such as gas solubility, solution gas, and bubble point pressure.
This document provides an overview of methods for calculating key reservoir fluid properties including: oil formation volume factor (Bo), gas solubility (Rs), bubble point pressure (Pb), oil density, and oil compressibility (Co). It describes several commonly used correlations for determining these properties as functions of temperature, pressure, gas and oil specific gravities. The correlations compared include those developed by Standing, Vasquez-Beggs, Glaso, Marhoun, and Petrosky-Farshad. The document also addresses calculating fluid properties for both undersaturated and saturated oil conditions.
This document discusses material balance applied to oil reservoirs. It introduces the Schilthuis material balance equation, which is a basic tool for interpreting and predicting reservoir performance. The general form of the material balance equation accounts for underground withdrawal of oil and gas, expansion of oil and originally dissolved gas, expansion of any gas cap gas, and changes in hydrocarbon pore volume due to water and pore volume changes. The document provides the specific equations that make up the material balance and shows how it can be simplified for different reservoir drive mechanisms, including solution gas drive above and below the bubble point pressure. It also provides examples of calculating recovery factors and gas saturation from the material balance equation for a reservoir undergoing primary depletion by solution gas drive.
This document discusses laboratory experiments for analyzing reservoir fluid properties, including differential liberation (vaporization) tests and separator tests. Differential liberation tests measure properties such as gas and oil volumes, densities, and compositions as pressure is reduced, better simulating reservoir separation. Separator tests determine volumetric behavior as fluids pass through surface separation, providing data to optimize conditions and calculate petroleum engineering parameters. The document explains procedures, calculations, and objectives of the tests.
This document discusses methods for calculating hydrocarbon volumes in reservoirs, including volumetric and material balance methods. It provides details on calculating oil, gas, and total hydrocarbon volumes based on parameters like porosity, net thickness, and saturation. It also covers reservoir drive mechanisms that can provide energy for hydrocarbon production, such as solution gas drive, gas cap drive, water drive, compaction drive, and combination drives. Reservoir performance data like pressure trends and gas-oil ratios can help identify the active drive mechanism.
Group Project- An extract from original reportMukesh Mathew
油
1. PVT analysis was carried out on samples from three wells to determine reservoir properties like bubble point pressure, solution gas-oil ratio, oil composition and volume factors. The analysis found the oil to have a stock tank gravity of 33.9-34.1 API and be mainly composed of methane and heptanes+.
2. Core data from three wells was analyzed statistically to find average porosity and permeability ranges of 15-21% and 210-350mD respectively. Capillary pressure and relative permeability curves were also generated from core and SCAL data.
3. Normalization of capillary pressure data using the modified Leverett J-function allowed the creation of a single curve for use in reservoir modeling
The document discusses the differential liberation (vaporization) test, which simulates the separation process that occurs as reservoir fluids flow from the reservoir to the surface. The test involves gradually reducing the pressure in a visual PVT cell containing a reservoir oil sample and measuring the volume of gas liberated at each step. Key data collected includes the amount of gas in solution, oil volume shrinkage, gas composition and properties, and remaining oil density as functions of pressure. Differential oil formation volume factors and solution gas-oil ratios are calculated from the experimental data but must not be confused with actual PVT properties due to the test simulating differential behavior.
This document provides an overview of advanced well testing concepts and objectives. It aims to upgrade engineers' knowledge to prepare them for professional well testing positions. Key topics covered include: linking measurement data to customer decisions; understanding well testing equipment; preparing for different well conditions; and qualifying engineers to discuss business plans with customers. The course outlines topics such as reservoir properties, well testing purposes and equipment, testing various well types, and meeting customer needs for each test.
This document provides an overview of advanced well testing concepts and objectives. It aims to upgrade engineers' knowledge to prepare them for professional well testing positions. Key topics covered include: linking measurement data to customer decisions; understanding well testing equipment; preparing for different well conditions; and qualifying engineers to discuss business plans with customers. The course outlines topics such as reservoir properties, well testing purposes and equipment, testing various well types, and meeting customer needs for each test.
This document provides an overview of advanced well testing concepts and objectives. It aims to upgrade engineers' knowledge to prepare them for professional well testing positions. Key topics covered include: linking measurement data to customer decisions; understanding well testing equipment; preparing for different well conditions; and qualifying engineers to discuss business plans with customers. The course outlines topics such as reservoir properties, well testing purposes and equipment, testing various well types, and meeting customer needs for each test.
Improving Surgical Robot Performance Through Seal Design.pdfBSEmarketing
油
Ever wonder how something as "simple" as a seal can impact surgical robot accuracy and reliability? Take quick a spin through this informative deck today, and use what you've learned to build a better robot tomorrow.
This document provides an overview of key concepts in reservoir fluid properties including:
- Formation volume factors (Bo and Bt) which relate the volume of oil and gas in the reservoir to stock tank conditions.
- Methods for determining PVT properties like gas solubility and Bo/Bt through laboratory experiments as pressure changes.
- Key fluid properties like bubble point pressure, compressibility, and molecular weight that impact reservoir performance.
- Techniques for estimating fluid properties using correlations with parameters like boiling point and API gravity.
This document outlines topics covered in a reservoir engineering course, including reservoir fluid behaviors, properties of petroleum reservoirs, gas behavior, and properties of crude oil systems. It specifically discusses properties of interest like density, solution gas, bubble point pressure, formation volume factor, viscosity and more. It provides empirical correlations to estimate properties like gas solubility, bubble point pressure, and formation volume factor as a function of parameters like solubility, gas gravity, oil gravity and temperature. The document is focused on understanding physical properties of crude oil and gas reservoirs which is important for reservoir engineering applications and problem solving.
This document provides an overview of methods for calculating reservoir fluid properties, including crude oil and water properties. It discusses calculating the total formation volume factor (Bt) using correlations like Standing's and Glaso's. It also covers calculating crude oil viscosity, including dead-oil viscosity using Beal's correlation, saturated oil viscosity using Chew-Connally, and undersaturated oil viscosity using Vasquez-Beggs. The document provides equations and discusses experimental data ranges for various fluid property correlations.
This document describes procedures for analyzing reservoir fluid properties in the laboratory, including crude oil properties, water properties, and various laboratory tests. It discusses measuring the total formation volume factor, viscosity, surface tension, and other properties of crude oil and water. It also describes primary tests conducted on-site, routine laboratory tests like compositional analysis and constant-composition expansion, and special laboratory PVT tests. The constant-composition expansion test measures saturation pressure and compressibility by reducing pressure in a cell and measuring volume changes. The results are used to calculate fluid densities and compressibility coefficients above the saturation pressure.
Chapter 2 basic single phase-flow equationMichaelDang47
油
This document provides an overview of the derivation and development of the basic single-phase flow equations in reservoir simulation. It begins with the conservation principles of mass and momentum and the Darcy's law constitutive relationship. It then presents the continuity and single-phase flow equations for one-dimensional horizontal flow. Finally, it provides the 3D single-phase flow equation and a table of relevant quantities in the flow equations.
This document provides an overview of reservoir fluid properties including:
1. Crude oil properties such as density, gas solubility, bubble point pressure, formation volume factor, compressibility, and correlations to calculate these properties.
2. Water properties including water formation volume factor, viscosity, gas solubility in water, and water isothermal compressibility.
3. The total formation volume factor and viscosity of crude oil are also discussed along with definitions of dead-oil, saturated-oil, and undersaturated oil viscosities.
The document discusses laboratory analysis techniques for gas condensate systems, including recombination and analysis of separator samples, constant-composition expansion tests, and constant-volume depletion tests. It describes the procedures for these various laboratory experiments in detail, including determining fluid properties like compressibility factors and calculating quantities like retrograde liquid saturation and cumulative gas production. The goal is to better understand the pressure-volume-temperature behavior and compositional changes that occur during depletion of a gas condensate reservoir.
This document provides an overview of key reservoir fluid properties including methods for calculating z-factors, gas properties such as compressibility and viscosity, crude oil properties like density and solution gas, and empirical correlations for determining properties like gas solubility, bubble point pressure, and formation volume factors. The document discusses various correlations for estimating properties in the absence of laboratory measurements and defines important concepts such as gas solubility, solution gas, and bubble point pressure.
This document provides an overview of methods for calculating key reservoir fluid properties including: oil formation volume factor (Bo), gas solubility (Rs), bubble point pressure (Pb), oil density, and oil compressibility (Co). It describes several commonly used correlations for determining these properties as functions of temperature, pressure, gas and oil specific gravities. The correlations compared include those developed by Standing, Vasquez-Beggs, Glaso, Marhoun, and Petrosky-Farshad. The document also addresses calculating fluid properties for both undersaturated and saturated oil conditions.
This document discusses material balance applied to oil reservoirs. It introduces the Schilthuis material balance equation, which is a basic tool for interpreting and predicting reservoir performance. The general form of the material balance equation accounts for underground withdrawal of oil and gas, expansion of oil and originally dissolved gas, expansion of any gas cap gas, and changes in hydrocarbon pore volume due to water and pore volume changes. The document provides the specific equations that make up the material balance and shows how it can be simplified for different reservoir drive mechanisms, including solution gas drive above and below the bubble point pressure. It also provides examples of calculating recovery factors and gas saturation from the material balance equation for a reservoir undergoing primary depletion by solution gas drive.
This document discusses laboratory experiments for analyzing reservoir fluid properties, including differential liberation (vaporization) tests and separator tests. Differential liberation tests measure properties such as gas and oil volumes, densities, and compositions as pressure is reduced, better simulating reservoir separation. Separator tests determine volumetric behavior as fluids pass through surface separation, providing data to optimize conditions and calculate petroleum engineering parameters. The document explains procedures, calculations, and objectives of the tests.
This document discusses methods for calculating hydrocarbon volumes in reservoirs, including volumetric and material balance methods. It provides details on calculating oil, gas, and total hydrocarbon volumes based on parameters like porosity, net thickness, and saturation. It also covers reservoir drive mechanisms that can provide energy for hydrocarbon production, such as solution gas drive, gas cap drive, water drive, compaction drive, and combination drives. Reservoir performance data like pressure trends and gas-oil ratios can help identify the active drive mechanism.
Group Project- An extract from original reportMukesh Mathew
油
1. PVT analysis was carried out on samples from three wells to determine reservoir properties like bubble point pressure, solution gas-oil ratio, oil composition and volume factors. The analysis found the oil to have a stock tank gravity of 33.9-34.1 API and be mainly composed of methane and heptanes+.
2. Core data from three wells was analyzed statistically to find average porosity and permeability ranges of 15-21% and 210-350mD respectively. Capillary pressure and relative permeability curves were also generated from core and SCAL data.
3. Normalization of capillary pressure data using the modified Leverett J-function allowed the creation of a single curve for use in reservoir modeling
The document discusses the differential liberation (vaporization) test, which simulates the separation process that occurs as reservoir fluids flow from the reservoir to the surface. The test involves gradually reducing the pressure in a visual PVT cell containing a reservoir oil sample and measuring the volume of gas liberated at each step. Key data collected includes the amount of gas in solution, oil volume shrinkage, gas composition and properties, and remaining oil density as functions of pressure. Differential oil formation volume factors and solution gas-oil ratios are calculated from the experimental data but must not be confused with actual PVT properties due to the test simulating differential behavior.
This document provides an overview of advanced well testing concepts and objectives. It aims to upgrade engineers' knowledge to prepare them for professional well testing positions. Key topics covered include: linking measurement data to customer decisions; understanding well testing equipment; preparing for different well conditions; and qualifying engineers to discuss business plans with customers. The course outlines topics such as reservoir properties, well testing purposes and equipment, testing various well types, and meeting customer needs for each test.
This document provides an overview of advanced well testing concepts and objectives. It aims to upgrade engineers' knowledge to prepare them for professional well testing positions. Key topics covered include: linking measurement data to customer decisions; understanding well testing equipment; preparing for different well conditions; and qualifying engineers to discuss business plans with customers. The course outlines topics such as reservoir properties, well testing purposes and equipment, testing various well types, and meeting customer needs for each test.
This document provides an overview of advanced well testing concepts and objectives. It aims to upgrade engineers' knowledge to prepare them for professional well testing positions. Key topics covered include: linking measurement data to customer decisions; understanding well testing equipment; preparing for different well conditions; and qualifying engineers to discuss business plans with customers. The course outlines topics such as reservoir properties, well testing purposes and equipment, testing various well types, and meeting customer needs for each test.
Improving Surgical Robot Performance Through Seal Design.pdfBSEmarketing
油
Ever wonder how something as "simple" as a seal can impact surgical robot accuracy and reliability? Take quick a spin through this informative deck today, and use what you've learned to build a better robot tomorrow.
Algorithm design techniques include:
Brute Force
Greedy Algorithms
Divide-and-Conquer
Dynamic Programming
Reduction / Transform-and-Conquer
Backtracking and Branch-and-Bound
Randomization
Approximation
Recursive Approach
What is an algorithm?
An Algorithm is a procedure to solve a particular problem in a finite number of steps for a finite-sized input.
The algorithms can be classified in various ways. They are:
Implementation Method
Design Method
Design Approaches
Other Classifications
In this article, the different algorithms in each classification method are discussed.
The classification of algorithms is important for several reasons:
Organization: Algorithms can be very complex and by classifying them, it becomes easier to organize, understand, and compare different algorithms.
Problem Solving: Different problems require different algorithms, and by having a classification, it can help identify the best algorithm for a particular problem.
Performance Comparison: By classifying algorithms, it is possible to compare their performance in terms of time and space complexity, making it easier to choose the best algorithm for a particular use case.
Reusability: By classifying algorithms, it becomes easier to re-use existing algorithms for similar problems, thereby reducing development time and improving efficiency.
Research: Classifying algorithms is essential for research and development in computer science, as it helps to identify new algorithms and improve existing ones.
Overall, the classification of algorithms plays a crucial role in computer science and helps to improve the efficiency and effectiveness of solving problems.
Classification by Implementation Method: There are primarily three main categories into which an algorithm can be named in this type of classification. They are:
Recursion or Iteration: A recursive algorithm is an algorithm which calls itself again and again until a base condition is achieved whereas iterative algorithms use loops and/or data structures like stacks, queues to solve any problem. Every recursive solution can be implemented as an iterative solution and vice versa.
Example: The Tower of Hanoi is implemented in a recursive fashion while Stock Span problem is implemented iteratively.
Exact or Approximate: Algorithms that are capable of finding an optimal solution for any problem are known as the exact algorithm. For all those problems, where it is not possible to find the most optimized solution, an approximation algorithm is used. Approximate algorithms are the type of algorithms that find the result as an average outcome of sub outcomes to a problem.
Example: For NP-Hard Problems, approximation algorithms are used. Sorting algorithms are the exact algorithms.
Serial or Parallel or Distributed Algorithms: In serial algorithms, one instruction is executed at a time while parallel algorithms are those in which we divide the problem into subproblems and execute them on different processors.
Defining the Future of Biophilic Design in Crete.pdfARENCOS
油
Biophilic design is emerging as a key approach to enhancing well-being by integrating natural elements into residential architecture. In Crete, where the landscape is rich with breathtaking sea views, lush olive groves, and dramatic mountains, biophilic design principles can be seamlessly incorporated to create healthier, more harmonious living environments.
Flex and rigid-flex printed circuit boards (PCBs) can be considered at the basic level some of the most complex PCBs in the industry. With that in mind, its incredibly easy to make a mistake, to leave something out, or to create a design that was doomed from the start.
Such design failures can end up leading to an eventual failure by delamination, short circuits, damage to the flex portions, and many other things. The easiest way to circumvent these is to start at the beginning, to design with preventing failure in mind rather than trying to fix existing designs to accommodate for problems.
In this webinar, we cover how to design flex and rigid-flex PCBs with failure prevention in mind to save time, money, and headaches, and what failure can look like.
For more information on our flex and rigid-flex PCB solutions, visit https://www.epectec.com/flex.
The Golden Gate Bridge a structural marvel inspired by mother nature.pptxAkankshaRawat75
油
The Golden Gate Bridge is a 6 lane suspension bridge spans the Golden Gate Strait, connecting the city of San Francisco to Marin County, California.
It provides a vital transportation link between the Pacific Ocean and the San Francisco Bay.
The Uni-Bell PVC Pipe Association (PVCPA) has published the first North American industry-wide environmental product declaration (EPD) for water and sewer piping, and it has been verified by NSF Sustainability, a division of global public health organization NSF International.
Indian Soil Classification System in Geotechnical EngineeringRajani Vyawahare
油
This PowerPoint presentation provides a comprehensive overview of the Indian Soil Classification System, widely used in geotechnical engineering for identifying and categorizing soils based on their properties. It covers essential aspects such as particle size distribution, sieve analysis, and Atterberg consistency limits, which play a crucial role in determining soil behavior for construction and foundation design. The presentation explains the classification of soil based on particle size, including gravel, sand, silt, and clay, and details the sieve analysis experiment used to determine grain size distribution. Additionally, it explores the Atterberg consistency limits, such as the liquid limit, plastic limit, and shrinkage limit, along with a plasticity chart to assess soil plasticity and its impact on engineering applications. Furthermore, it discusses the Indian Standard Soil Classification (IS 1498:1970) and its significance in construction, along with a comparison to the Unified Soil Classification System (USCS). With detailed explanations, graphs, charts, and practical applications, this presentation serves as a valuable resource for students, civil engineers, and researchers in the field of geotechnical engineering.
Indian Soil Classification System in Geotechnical EngineeringRajani Vyawahare
油
mat_bal of reservoir engineering program.pptx
1. Material Balance for Oil Reservoirs
Md. Mehedi Hasan
Lecturer, Dept. of PME
Jessore University of Science and Technology (JUST)
2. Uses of material balance
Material balance calculations can be used to:
Determine original oil and gas in place in the reservoir;
Determine original water in place in the aquifer;
Estimate expected oil and gas recoveries as a function of pressure
decline in a closed reservoir producing by depletion drive, or as a
function of water influx in a water-drive reservoir;
Predict future behavior of a reservoir (production rates, pressure
decline, and water influx);
Verify volumetric estimates of original fluids in place;
Verify future production rates and recoveries predicted by
decline-curve analysis;
Determine which primary producing drive mechanisms are
responsible for a reservoir's observed behavior, and quantify the
relative importance of each mechanism;
Evaluate the effectiveness of a water drive;
Study the interference of fields sharing a common aquifer.
3. Assumption for Material Balance
The material balance equations considered assume tank type
behavior at any given datum depth
The reservoir is considered to have the same pressure and fluid
properties at any location in the reservoir.
This assumption is quite reasonable provided that quality
production and static pressure measurements are obtained.
Reservoir consider homogeneous porosity permeability
4. The Material Balance Equation
The equation can be written on volumetric basis
as:
Initial volume = volume remaining + volume removed
Before deriving the material balance, it is convenient
to denote certain terms by symbols for brevity. The
symbols used conform where possible to the standard
nomenclature adopted by the Society of
Petroleum Engineers (SPE)
5. Basic Principle
p1 > p2 p3 p4
> >
Undersaturated
oil
Bubble
point
Expanding
Gas Cap
Liquid shrinking
due to liberation
of dissolved gas
Oil
+
dissolved
gas
Initial gas cap Expanded gas cap
Expanded of oil +
dissolved gas
Reduction in PV due to
increased grain packing
and connate water
expansion
Pinit P
>
6. The Material Balance Equation
Terms Symbols
Initial reservoir pressure, psi Pi
Change in reservoir pressure = pi p, psi p
Bubble point pressure, psi Pb
Initial (original) oil in place, STB N
Cumulative oil produced, STB Np
Cumulative water produced, bbl Wp
Cumulative gas produced, scf Gp
Cumulative gas-oil ratio, scf/STB Rp
Instantaneous gas-oil ratio, scf/STB GOR
Initial gas solubility, scf/STB Rsi
Gas solubility, scf/STB Rs
7. The Material Balance Equation
Terms Symbols
Initial oil formation volume factor, bbl/STB Boi
Oil formation volume factor, bbl/STB Bo
Initial gas formation volume factor, bbl/scf Bgi
Gas formation volume factor, bbl/scf Bg
Cumulative water injected, STB Winj
Cumulative gas injected, scf Ginj
Cumulative water influx, bbl We
Ratio of initial gas-cap-gas reservoir volume to
initial reservoir oil volume , bbl/bbl
m
Initial gas-cap gas, scf G
Pore volume, bbl P.V
8. The Material Balance Equation
Terms Symbols
Water compressibility, psi1 cw
Formation (rock) compressibility, psi1 cf
Gas formation volume factor of the gas cap gas ,bbl/scf Bg c
Gas formation volume factor of the solution gas
,bbl/scf
Bg s
Cumulative gas production from gas cap Gpc
Cumulative gas production from solution gas
. Gps
9. In this lecture we will derive the material balance as a
volumetric balance. Material balance is also a critical step
in modern reservoir simulation where a mass balance of
components within the different fluid phases is generally
performed.
Pinit P
>
A
B
Oil +
dissolved
gas
Gas cap
C
wl = Expansion of oil + originally
dissolved gas (B) (rb)
+ Expansion of gascap gas(A)(rb)
+ Reduction in PV due to
expansion of connate water
and tighter grain packing(C)(rb)
that the volume balance is written in terms of fluid at
oir conditions or as underground withdrawl and
pansion.
The Material Balance Equation
10. Data available to do material balance
Production Data
Np = Cumulative oil volume produced (stb)
Rp = Cumulative gas-oil ratio
=
PVT properties
Bo = Oil FVF (bbl/STB)
Bg = Gas FVF (cu.ft/SCF)
Bw = Water FVF(bbl/STB)
Cw = Compressibility of water (psi-1
)
Rso = Solution Gas-Oil Ratio
Reservoir properties
Cf = Rock Compressibility
Swi = Connate water saturation
(stb)
produced
oil
of
volume
Cum.
(scf)
produced
gas
of
volume
Cum.
11. Data available to do material balance (Cont.)
N = Initial volume of oil in reservoir (rb)
= (stb)
m = Initial gas cap
=
These are listed as other parameters because these may
either be known by wireline logs, reservoir modeling etc.
Or they may be the objective of the material balance
computation.
(rb)
oil
of
n volume
hydrocarbo
Initial
(rb)
gap
gas
of
n volume
hydrocarbo
Initial
oi
wc B
S
V /
)
1
(
12. Derivation of the material balance
Expansion of the oil + liberated gas
mponents:
nsion of oil:
Initial Oil = N (stb)
Initial oil at reservoir conditions = N Boi (rb)
Volume of oil at reduced pressure p = N Bo (rb)
Net oil expansion = N(Bo-Boi) (rb)
nsion of liberated gas:
issolved at initial condition = NRsi (scf)
issolved at reduced pressure p = NRs (scf)
ated gas = N(Rsi-Rs) (scf)
me of gas at reservoir conditions= N(Rsi-Rs)Bg (rb)
13. Derivation of the material balance
Expansion of the gas cap gas
Expansion of the gascap gas = gascap gas (at p) gascap (at pi)
RB
SCF
RB
SCF
B
B
mNB
p
at
gas
of
Amount
SCF
SCF
RB
RB
B
mNB
G
or
RB
SCF
RB
STB
SCF
SCF
mNB
gas
gascap
of
volume
total
The
g
gi
oi
gi
oi
oi
]
[
]
[
1
)
(
]
[
1
]
[
1
]
[
]
[
)
3
.
3
(
)
(
)
1
(
]
[
RB
B
B
mNB
RB
mNB
B
B
mNB
gas
gascap
the
of
Expansion
gi
g
oi
oi
gi
g
oi
14. Derivation of the material balance (Cont.)
Change in the HCPV due to the connate water
expansion & pore volume reduction
p
S
c
S
c
NB
m
p
c
S
c
S
mNBoi
NBoi
p
c
S
c
S
HCPV
p
c
S
c
V
p
V
c
S
V
c
S
V
vol
water
connate
the
V
p
V
c
V
c
S
HCPV
vol
pore
total
the
V
dV
dV
HCPV
d
wc
f
wc
w
oi
f
wc
w
w
f
wc
w
w
f
wc
w
f
f
f
wc
f
w
wc
f
w
f
f
w
w
w
f
f
w
)
1
(
)
1
(
)
(
)
1
(
)
(
)
1
(
)
(
)
(
.
)
(
)
1
/(
.
)
(
15. Derivation of the material balance (Cont.)
Underground withdrawal
]
)
(
[
)
(
)
(
)
(
)
(
)
(
)
(
Pr
g
s
p
o
p
g
s
p
p
o
p
g
s
p
p
p
o
p
p
p
p
B
R
R
B
N
B
R
R
N
B
N
withdrawal
d
Undergroun
gas
RB
B
R
N
R
N
oil
RB
B
N
withdrawal
d
Undergroun
gas
SCF
R
N
oil
STB
N
surface
at
oduction
16. Derivation of the material balance (Cont.)
Withdrawal = Expansion of oil +originally (rb) dissolved gas (B)
(rb) + Expansion of gascap gas(A)(rb) + Reduction in HCPV due
to expansion of connate water and tighter grain packing(C)(rb)
際際滷: 15=12+13+14
17. The general expression for the material balance as
w
p
e
wc
f
wc
w
oi
gi
g
oi
g
s
si
oi
o
g
s
p
o
p
B
W
W
p
S
c
S
c
NB
m
B
B
mNB
B
R
R
N
B
B
N
B
R
R
B
N
)
(
)
1
(
)
1
(
)
1
(
)
(
)
(
]
)
(
[
)
7
.
3
(
)
(
1
)
1
(
1
)
(
)
(
]
)
(
[
w
p
e
wc
f
wc
w
gi
g
oi
g
s
si
oi
o
oi
g
s
p
o
p
B
W
W
p
S
c
S
c
m
B
B
m
B
B
R
R
B
B
NB
B
R
R
B
N
p
measuring
difficulty
Main
p
V
c
dV
fluids
reservoir
of
Expansion
oduction
form
Simple
t
p
f
W
p
f
B
R
B
Note
e
g
s
o
:
Pr
:
)
,
(
)
(
,
,
:
18. Features of MBE
It is zero dimensional, meaning that it is
evaluated at a point in the reservoir
Lack of time dependence
Pressure only appears explicitly in the water and
pore compressibility.
Water influx is pressure and time depended
parameter
The equation is always evaluated in the way it
was derived by comparing the current volumes at
pressure P to the original volumes at Pi. It is not
evaluated in steps wise or differential fashion.
19. The general expression for the material balance as
w
p
e
wc
f
wc
w
oi
gi
g
oi
g
s
si
oi
o
g
s
p
o
p
B
W
W
p
S
c
S
c
NB
m
B
B
mNB
B
R
R
N
B
B
N
B
R
R
B
N
)
(
)
1
(
)
1
(
)
1
(
)
(
)
(
]
)
(
[
)
7
.
3
(
)
(
1
)
1
(
1
)
(
)
(
]
)
(
[
w
p
e
wc
f
wc
w
gi
g
oi
g
s
si
oi
o
oi
g
s
p
o
p
B
W
W
p
S
c
S
c
m
B
B
m
B
B
R
R
B
B
NB
B
R
R
B
N
F
E Eg
E f w
w
p
e
w B
W
WeB
20. where
)
12
.
3
(
)
( ,
w
e
w
f
g
o B
W
mE
mE
E
N
F
STB
RB
p
S
c
S
c
B
m
E
STB
RB
B
B
B
E
STB
RB
B
R
R
B
B
E
RB
B
W
B
R
R
B
N
F
wc
f
wc
w
oi
w
f
gi
g
oi
g
g
s
si
oi
o
o
w
p
g
s
p
o
p
)
1
(
)
1
(
]
[
)
1
(
]
[
)
(
)
(
]
[
]
)
(
[
,
Material Balance Expressed as a Liner Equation
21. No initial gascap, negligible water influx
With water influx eq(3.12) becomes
Eq.(3.12) having a combination drive-all possible sources of energy.
0
&
w
f c
c
)
13
.
3
(
)
12
.
3
.(
o
NE
F
Eq
)
14
.
3
(
o
e
o E
W
N
E
F
)
12
.
3
(
)
( ,
w
e
w
f
g
o B
W
mE
mE
E
N
F
Material Balance Expressed as a Liner Equation (Cont.)
22. 則 3.4 Reservoir Drive Mechanisms
- Solution gas drive
- Gascap drive
-Natural water
drive
- Compaction drive
In terms of
-reducing the M.B to a compact form to
quantify reservoir performance
-determining the main producing
characteristics,
for example, GOR; water cut
-determining the pressure decline in the
reservoir
- estimating the primary recovery factor
Reservoir drive mechanism
24. Above the B.P. pressure
- no initial gascap, m=0
- no water flux, We=0 ; no water production, Wp=0
- Rs=Rsi=Rp
from eq.(3.7)
)
7
.
3
(
)
(
1
)
1
(
1
)
(
)
(
]
)
(
[
w
p
e
wc
f
wc
w
gi
g
oi
g
s
si
oi
o
oi
g
s
p
o
p
B
W
W
p
S
c
S
c
m
B
B
m
B
B
R
R
B
B
NB
B
R
R
B
N
0
;
0
;
0
;
0
)
(
;
0
)
(
:
p
e
s
si
s
p W
W
m
R
R
R
R
Note
ility
compressib
weighted
saturation
effective
the
S
c
S
c
S
c
c
where
S
S
p
c
NB
B
N
or
p
B
B
B
p
B
B
B
p
S
c
S
c
S
c
NB
B
N
dp
dB
B
dp
dV
V
c
p
S
c
S
c
c
NB
B
N
p
S
c
s
c
B
B
B
NB
B
N
wc
f
w
w
o
o
e
wc
o
e
oi
o
p
oi
oi
o
oi
o
oi
wc
f
w
w
o
o
oi
o
p
o
o
o
o
o
wc
f
w
w
o
oi
o
p
wc
f
wc
w
oi
oi
o
oi
o
p
,
1
1
)
18
.
3
(
)
(
)
(
)
17
.
3
(
)
1
(
1
1
)]
1
(
[
]
1
)
(
)
(
[
25. Exercise3.1 Solution gas drive, undersaturated oil reservoir
Determine R.F.
Solution:
FromTable2.4(p.65)
2
.
0
10
6
.
8
10
3
)
65
.
(
4
.
2
1
6
1
6
w
f
w
b
i
S
psi
c
psi
c
p
table
PVT
p
p
p
if
STB
RB
B
psi
p
STB
RB
B
psi
p
ob
b
oi
i
12511
,
3330
2417
.
1
,
4000
1
6
10
3
.
11
)
3330
4000
(
2417
.
1
2417
.
1
2511
.
1
1
1
psi
p
B
B
B
c
dp
dB
B
dp
dV
V
c
oi
oi
ob
o
o
o
o
o
o
Eq(3.18)
%
5
.
1
015
.
0
)
3330
4000
(
10
8
.
22
2511
.
1
2417
.
1
.
.
6
p
c
B
B
N
N
F
R
p
c
NB
B
N
e
ob
oi
Pb
p
e
oi
o
p )
1
)(
1
/(
1
wc
f
w
w
o
o
S
c
S
c
S
c
Swc
Ce
32. Below B.P. pressure (Saturation oil)
P<Pb =>gas liberated from saturated oil
1
6
1
6
1
6
1
6
1
6
10
6
.
8
10
3
10
3
.
11
10
300
10
300
3300
1
1
1
psi
c
psi
c
psi
c
psi
c
psi
P
p
c
f
w
o
g
b
g
33. Exercise 3.2 Solution gas drive; below bubble point pressure
Reservoir-described in exercise 3.1
Pabandon = 900psia
(1) R.F = f(Rp)? Conclusion?
(2) Sg(free gas) = F(Pabandon)?
Solution:
(1) From eq(3.7)
)
7
.
3
(
)
(
1
)
1
(
1
)
(
)
(
]
)
(
[
w
p
e
wc
f
wc
w
gi
g
oi
g
s
si
oi
o
oi
g
s
p
o
p
B
W
W
p
S
c
S
c
m
B
B
m
B
B
R
R
B
B
NB
B
R
R
B
N
developed
is
S
if
negligible
is
p
S
c
S
c
NB
W
W
cap
gas
initial
no
m
P
B
below
gas
solution
for
g
wc
f
wc
w
oi
p
e
)
1
(
0
;
0
0
.
.
34. Eq(3.7) becomes
)
20
.
3
(
]
)
(
)
[(
]
)
(
[
g
s
si
oi
o
g
s
p
o
p B
R
R
B
B
N
B
R
R
B
N
201
344
00339
.
0
)
122
(
0940
.
1
00339
.
0
)
122
510
(
)
2417
.
1
0940
.
1
(
.
.
)
(
)
(
)
(
.
.
900
900
p
p
p
p
p
g
s
p
o
g
s
si
oi
o
p
R
R
N
N
F
R
B
R
R
B
B
R
R
B
B
N
N
F
R
Conclusion:
Rp
RF
1
49
.
0
%
49
500
)
85
.
(
3
.
3
.
900
N
N
STB
SCF
R
p
Fig
From
p
p
36. (2) the overall gas balance
)
21
.
3
(
)
1
(
)]
(
)
(
[
)
(
)
1
(
)
1
(
1
oi
wc
g
s
p
p
s
si
g
g
s
p
g
p
p
g
si
wc
g
oi
b
wc
wc
oi
NB
S
B
R
R
N
R
R
N
S
B
R
N
N
B
R
N
B
NR
S
S
NB
p
p
for
S
HCPV
volume
pore
S
NB
liberated
gas in the
reservoir
total
amount
of gas
gas
produced
at surface
gas still
dissolved
in the oil
= -
4428
.
0
8
.
0
00339
.
0
2417
.
1
)]
122
500
(
49
.
0
)
122
510
[(
)
1
(
)]
(
)
[(
)
1
(
)]
(
)
(
[
wc
g
oi
s
p
p
s
si
oi
wc
g
s
p
s
si
g S
B
B
R
R
N
N
R
R
NB
S
B
R
R
Np
R
R
N
S
40. Exercise 3.3 (Cont.)
To produced 10,000stb/d oil initial injection rate
4X10,000 = 40,000 rb/d water required
70 % water needed to displace the liberated gas
Above bubble point 1.2511x 10,000 =12500 b/d
42. Gascap Drive
Under initial conditions the oil at the gas oil contract must be at
saturation or bubble point pressure.
The oil further downdip becomes progressively less saturated at the
higher pressure and temperature.
Assuming , natural water influx is negligible (We= 0)
Gas compressibility >> than formation, so its also negligible
43. Gascap Drive (Cont.)
The right side of Equation 3.23,describing the expansion of oil plus
originally dissolved gas
The solution gas drive mechanism active with oil column.
For better understanding , Havlena aand Odeh derive a simple form of
above equation
F= N(Eo + mEg)--------------------------------3.24
F=Np(Bo+(Rp-Rs)Bg)
Eo= (Bo-Boi) + (Rsi-Rs)Bg
Eg= Boi(Bg/Bgi 1)
If the correct value of m taken , the line must be in straight line.
45. Exercise 3.4
The gascap reservoir shown in fig. 3.6 is estimated, from volumetric
calculations, to have had an initial oil volume N of 115 106 stb.
The cumulative oil production
Np and cumulative gas oil ratio Rp are listed in table 3.1, as
functions of the average reservoir pressure, over the first few years
of production. (Also listed are the relevant PVT data, again taken
from table 2.4, under the assumption that, for this particular
application, Pi= Pb = 3330 psia).
46. Exercise 3.4 cont.
The size of the gascap is uncertain with the best
estimate, based on geological information, giving
the value of m = 0.4. Is this figure confirmed by
the production and pressure history? If not, what
is the correct value of m?
50. Exercise 3.4: Solution (Cont.)
For m=0.4; N= 132X10^6 stb
For m=0.5 ; N= 114X 10^6 stb
For m=0.6 ; N= 101X10^6 stb
If there uncertainty in the value of N and m then Havlna
and Odeh suggest that (eqn 3.24) re-expressed as
F/Eo = N + mN (Eg/Eo)
A plot F/Eo Vs Eg/Eo vs. Eg/Eo should be linear
intercept N
53. Natural Water Drive
Its different from water injection
A drop in the reservoir pressure, due to the production of the fluids ,
causes the aquifer water to expand and flow into the reservoir
Applying the compressibility definition to the aquifer than
Water Influx = Aquifer Compressibility X Initial Volume of
Water X Pressure Drop
Or, We = (Cw+Cf) Wi P
In which the total aquifer compressibility is the direct sum of
the water and pore compressibilities since the pore space is
entirely saturated with water.
If the aquifer small, its effect is not visible . Its only
applicable for large aquifer.
54. Natural Water Drive (Cont.)
Havlna and Odeh equation can be expressed as
F = N (Eo +m Eg + Ef,w ) + We
If the reservoir has no initial gascap, than the equation expressed as
F = N Eo + We
We = (Cw + Cf ) (re^2 ro^2 ) fh P
re and ro are the radii of the aquifer and reservoir.
56. Compaction Drive and Pore Compressibility
The compaction depends only upon the
difference between the vertically applied stress
(overburden ) and initial stress (fluid pressure )
At low grain pressure the compressibility of
the compacted sample is very high.