Skip to main content
main-content

Über dieses Buch

This book provides a clear and basic understanding of the concept of reservoir engineering to professionals and students in the oil and gas industry. The content contains detailed explanations of key theoretic and mathematical concepts and provides readers with the logical ability to approach the various challenges encountered in daily reservoir/field operations for effective reservoir management. Chapters are fully illustrated and contain numerous calculations involving the estimation of hydrocarbon volume in-place, current and abandonment reserves, aquifer models and properties for a particular reservoir/field, the type of energy in the system and evaluation of the strength of the aquifer if present. The book is written in oil field units with detailed solved examples and exercises to enhance practical application. It is useful as a professional reference and for students who are taking applied and advanced reservoir engineering courses in reservoir simulation, enhanced oil recovery and well test analysis.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract
Petroleum Engineering is a broad discipline with several areas of specializations such as petroleum geology, petrophysics, drilling engineering, mud and cementing, reservoir engineering, production (surface & subsurface) engineering, completion, formation evaluation, economics etc. These specialized areas work together as an integrated team to achieve one goal; to recover the hydrocarbon in a safe and cost-effective way. Petroleum engineering is one of the key aspects of Engineering that is concern with the exploration and production of hydrocarbons for consumption by human or to meet the host countries or global energy needs. This chapter presents an understanding of the essential features of petroleum reservoir, the job description of a reservoir engineer, the concept of drainage and imbibition processes, the hydrocarbon phase envelope and all its terminologies, identification of various types of reservoir fluids and their respective phase envelope/diagrams, understanding of the types of fluids in terms of flow regime and reservoir geometry and write the mathematical equations representing the flow regimes. Thus, for a better understanding of the flow regime, several solved example questions are given.
Sylvester Okotie, Bibobra Ikporo

Chapter 2. Resources and Reserves

Abstract
The heart of the oil and gas business is the amount of hydrocarbon reserves found initially in place, which implies that the value of the reserve estimation is a key driver for exploration and production companies to decide whether to develop or abandon a prospect/field based on their set criteria. There are several parties involved in the utilization of the hydrocarbon reserves and it includes the operating companies, regulatory bodies, banks, investors to mention a few for different reasons. Some of these reasons are: to obtain approvals from relevant ministries and other regulatory bodies, for investment in oil/gas sector, for exploration and development plan strategy and for facilities design. Other reasons include obtaining financing, evaluation of profit/interest, satisfying government regulations & taxation, etc. Furthermore, there are several uncertainties associated with hydrocarbon reserve estimation which are presented in the later part of this chapter, and when these uncertainties are not factored into the prospect evaluation, the result is a wrong estimation of the reserves. Accordingly, this chapter presents a detailed understanding of hydrocarbon resource and its classification, understanding of hydrocarbon reserve and its classification and a brief definition of reservoir characterization.
Sylvester Okotie, Bibobra Ikporo

Chapter 3. Volumetric Reserves Estimation

Abstract
An accurate estimation of oil and gas reserves is a key to the success of every field development, and this continues throughout the life of the field. There are several methods available for hydrocarbon reserves estimation and these are analogy, volumetric, decline analysis, material balance and reservoir simulation. The accuracy of any of these techniques depend solely on the type, quantity and quality of the geologic, geophysical, engineering, and economic data available plus the assumptions adopted for technical and commercial analysis. Also, the success of the reserve evaluation rely on the integrity, skill and judgment of the experienced professional evaluators. Thus, this chapter is basically dedicated for volumetric method of hydrocarbon reserve estimation which requires a limited amount of data. This chapter gives an understanding of the input parameters required and the factors affecting the volumetric reserves estimation. The step by step approach on how to calculate hydrocarbon reserves, bulk volume from Isopach map, condensate reserve calculations, an understanding of the deterministic and probabilities methods of reserves estimation are presented here with example cases.
Sylvester Okotie, Bibobra Ikporo

Chapter 4. Water Influx

Abstract
One of the forces responsible for the primary recovery of hydrocarbon, is the encroachment of a large pool of water body underlying the hydrocarbon accumulation in the reservoir structure. In the evaluation of hydrocarbon reservoir performance, it is paramount to accurately determine the amount of water encroaching into the reservoir whose value is dependent on the water viscosity, the permeability of the rock in the aquifer and the cross-sectional area between the water zone and the region where the hydrocarbon is accumulated. There are several analytical aquifer models presented in the past to estimate the amount of water encroaching into reservoirs, some of which can be applied to linear or radial aquifer, bottom aquifer and/or edge water, finite and/or infinite-acting. Van Everdingen & Hurst method requires the principle of superposition which is a tedious exercise, but it provides an exact solution to the radial diffusivity equation and can be applied at the early stage. The Carter-Tracy aquifer models can be applied to both finite and infinite-acting aquifers, it can be applied to both radial and linear aquifers and also applies to edge-water drive reservoirs only. Fetkovich model applies to both radial and linear aquifers, finite-acting aquifers, edge-water and bottom-water drive reservoirs. Thus, to understand the various aquifer models, several solved example questions and exercises are presented.
Sylvester Okotie, Bibobra Ikporo

Chapter 5. Material Balance

Abstract
Material balance is one of the key techniques for evaluating hydrocarbon reserves when production and pressure data from the field become available. It makes use of the basic concept of conservation of mass; which states that the cumulative observed production, expressed as an underground withdrawal, must be equal to the expansion of the fluids in the reservoir resulting from a finite pressure drop or expressed as the mass of fluids originally in place equal to mass of fluid remaining plus the mass of fluid produced. Material balance equation (MBE) is seen by the Reservoir Engineers as the basic tool for interpreting and predicting the performance of reservoirs. It helps them to get a feel of the reservoirs but has some limitations. There are several assumptions adopted in the derivation of the material balance equation and the implications which are presented herein. Therefore, to understand the material balance concept properly, several derivatives for oil and gas reservoirs to represent the general material balance equation under different conditions with multiple solved examples are presented in this chapter. Also the method of estimating the present gas-oil and oil-water contact are presented.
Sylvester Okotie, Bibobra Ikporo

Chapter 6. Linear Form of Material Balance Equation

Abstract
The complex nature of the material balance equation (MBE) used in estimation of oil and gas initially in place, cumulative aquifer/water influx, gas cap size and the contribution of the various drive mechanism was reduced to a simpler form by Havlena and Odeh (1963) to express the MBE in a straight line form. This involves rearranging the MBE into a linear equation. Therefore, the various mathematical model for the different material balance equations for the reservoir types in chapter five are represented in a straight line form in this chapter. To identify the type of reservoir in question, based on the signature of pressure history or behaviour and the production trend, Campbell and Dake developed a diagnostic plot and also to check for the presence and strength of aquifer. The plots were established based on the assumption of a volumetric reservoir, and deviation from this behaviour is used to indicate the reservoir type. Hence, the linear form of the material balance equations are presented for the various reservoir types with several solved example questions.
Sylvester Okotie, Bibobra Ikporo

Chapter 7. Decline Curve Analysis

Abstract
The oil and gas business is a high risk and challenging venture and despite this risk and uncertainties, several exploration and production operations are still going on in the Niger Delta region and other parts of the world. It is important to note that reserves is what drive the oil and gas business and every operator wants to produce his/her field in a safe and economic way without a rapid decline in the production rate. Thus, they wish to remain in their plateau stage for a long period. Decline curve analysis is key to determine the most probable life of a well or field and also estimate the future performance. This is important in determining the value of oil and gas economics. This chapter presents the various methods of decline curve analysis, the applications, the causes of production decline, factors affecting the decline rate and also the methods of identifying the decline model of any field from historical data. Several fields’ example questions and solutions to capture all the decline methods are also presented to determine the model parameter, forecast of future production, abandonment time and rate.
Sylvester Okotie, Bibobra Ikporo

Chapter 8. Pressure Regimes and Fluid Contacts

Abstract
The pressure of a reservoir is the key driving force for the primary recovery of hydrocarbon. It gives an indication of the amount of hydrocarbon remaining in the reservoir at any given time. Three types of pressure regime is encountered during the drilling process; which are the normal, abnormal and the subnormal pressure. During production of the hydrocarbon, as soon as the well is open to flow, the reservoir pressure starts declining, depending on the drive mechanism of the reservoir and at any point in time, the average value of pressure is estimated. In this chapter, solved example questions on determination of fluid contacts from pressure survey data and averaging of reservoir pressures are presented. In addition, the position of the reservoir fluid contact is not static as the fluid is produced. At first, the position of the fluid contacts are first determined within control wells and then extrapolated to other parts of the field. Once initial fluid contact elevations in control wells are determined, the contacts in other parts of the reservoir can be estimated. Hence, the various methods of estimating reservoir fluid contact are presented with solved example questions.
Sylvester Okotie, Bibobra Ikporo

Chapter 9. Inflow Performance Relationship

Abstract
Whenever a well is drilled and completed, it is expected to flow naturally via the wellbore to the surface, a relationship known as inflow and outflow. The inflow performance relationship (IPR) is often required for estimating well capacity, designing well completion, designing tubing string, optimizing well production, performing nodal analysis calculations, and designing artificial lift etc. This performance is commonly defined in terms of a plot of surface production rate versus bottomhole flowing pressure on a cartesian coordinate. The maximum flow rate that occurs when the bottomhole flowing pressure is zero and the maximum rate corresponding to this pressure is called the absolute open flow (AOF). In this chapter, several mathematical models for estimating the inflow performance relationship (IPR) are presented with solved example questions. Also, a case study of an improvement in IPR curve of well K35 to evaluate the efficacy of a pre and post stimulation job is also presented. Result indicates that; it is very important to determine the type of skin on each well. This help in knowing the type of solution to the problem of a well in order to increase its productivity. Thus, a well whose skin is due to completion, partial penetration or slanting of well does not require stimulation and if the field’s operators go ahead to stimulate, they will only end up wasting time and money without achieving any result because these types of skin cannot be removed by stimulation.
Sylvester Okotie, Bibobra Ikporo

Chapter 10. History Matching

Abstract
To develop a model that cannot accurately predict the past and present performance of a reservoir within a reasonable engineering tolerance of error is not a good model for predicting the future performance of the same reservoir. Hence, history matching is a process of adjusting key properties of the reservoir model to fit or match the actual historic or field data. It helps to identify the weaknesses in the available field data, it improves the reservoir description and forms the basis for the future performance predictions. To history a material balance model or reservoir simulation model, the known parameters to match or tune are the production data, PVT data, hydrocarbon properties, reservoir properties, and pressures while the unknown parameters are the water or aquifer influx and reserves (Stock tank oil initially in place, STOIIP). It is often difficult to perform history matching manually, thus, there are several simulators available to successfully history match a field with minimum tolerance of error. To achieve the desired objectives, several parameters such as rock data, fluid data, relative permeability data, pressure survey data to mention a few, need to be varied either singly or collectively to minimize the differences between the observed data and those calculated by the simulator. These variables are further quantified as low and high uncertainty. Also presented in this chapter, are the steps to match reservoir pressure, saturation, well productivity index, identification of history match problems and possible modifications and the methods of history matching.
Sylvester Okotie, Bibobra Ikporo

Chapter 11. Reservoir Performance Prediction

Abstract
Reservoir performance prediction is a key aspect of the oil and gas field development planning and reserves estimation which depicts the behaviour of the reservoir in the future; its success is dependent on accurate description of the reservoir rock properties, fluid properties, rock-fluid properties and flow performance. It therefore implies that engineers must have sound knowledge of the reservoir characteristics and production operations optimization and more importantly, to develop a mathematical model that will adequately depict the physical processes occurring in the reservoir such that the outcome of any action can be predicted within reasonable engineering tolerance of errors. Several Authors such as Muskat, Tarner’s, Tracy’s and Schilthuis developed a method of reservoir performance prediction based on material balance equation (MBE) by combining the appropriate MBE with the instantaneous GOR. These techniques are iterative and the calculations are repeated at a series of assumed reservoir pressure drops. These calculations are usually based on stock-tank barrel of oil-in-place at bubble point pressure and above the bubble point pressure, the cumulative oil produced is calculated directly from he material balance equations. In this chapter, the various mathematical models and algorithms for each technique are explicitly presented and validated with case studies. Also, at the end of the chapter, several exercises and references are given to further help strengthen readers understanding of the subject matter.
Sylvester Okotie, Bibobra Ikporo

Backmatter

Weitere Informationen