scholarly journals Analyzing of Drill Stem Test (DST) Result for Dual Porosity Limestone Reservoir

2017 ◽  
Vol 2 (3) ◽  
pp. 240-251
Author(s):  
Zheno Kareem Ahmed ◽  
Halkawt Ismail Ismail M-Amin
Keyword(s):  
Transient Flow ◽  
Double Porosity ◽  
Oil Field ◽  
Dual Porosity ◽  
Depth Interval ◽  
Reservoir Pressure ◽  
Well Test ◽  
Positive Skin ◽  
Skin Factor ◽  
Wellbore Storage

The aim of this paper is to discuss and evaluate the result of DST which was conducted in a limestone reservoir of an oil field at the depth interval 3764.29-3903.0 meter in well-1 to evaluate the dynamic characteristics of the reservoirs, for instance: skin effect, permeability, wellbore storage, reservoir boundary and average reservoir pressure. Reservoir Pressure profiles has been recorded for both Buildup and draw down intervals.  Semi-log and log-log coordinates have been used to plot the pressure signature date of both buildup period and its derivative to improve diagnostic and Horner plot. In addition, a dual porosity reservoir and infinite acting characteristic was discovered as a result of the well test data interpretation. Wellbore storage, skin factor and transient flow effects have been detected in the DST analysis on the dual porosity behavior due to phase re distribution.  Using final buildup sections, the flow parameters of dual porosity reservoir were determined as the flow between fissure and matrix was (7.558 x 10-6) while, the storability ratio between fissure and matrix was calculated as 0.3 and permeability is 102 MD for both matrix and the fissure together. However, negative value of skin factor mostly appears in double porosity limestone reservoirs, positive skin factor of the reservoir has been observed in this study. It can be considered that the positive skin factor can be resulted in either the formation was partially penetrated and /or wells were not cleaned up properly.

scholarly journals Analysis of DST to predict oil sand: A case study of Kailashtilla field

2016 ◽  
Vol 29 (1) ◽  
pp. 19-29
Author(s):  
Mohammad Amirul Islam ◽  
ASM Woobaidullah ◽  
Badrul Imam
Keyword(s):  
Transient Flow ◽  
Pressure Profile ◽  
Liquid Hydrocarbon ◽  
Depth Interval ◽  
Storage Effect ◽  
Reservoir Pressure ◽  
Oil Sand ◽  
Wellbore Storage ◽  
Flow Effects ◽  
Column Pressure

Drill Stem Test (DST) describes the dynamic characteristic of the hydrocarbon bearing formation such as wellbore storage, skin effect, permeability, average reservoir pressure and reservoir boundary. The wellbore storage effect and average reservoir pressure help to predict the flowing phase from the reservoir. An effort has been made to analyze the DST conducted in the Kailashtilla field at the depth interval 3261 meter to 3266 meter in well KTL-7. Two sets of pressure profile have been recorded. First conditioning the well for an hour then performed drawdown following pressure build-up. The pressure signature of the buildup period and its derivative is plotted on semi-log and log-log coordinates to develop Horner and diagnostic plots, respectively. Wellbore storage, skin and transient flow effects have been observed in the DST analysis which is an indication of the hydrocarbon bearing reservoir in the zone of interest. The value of wellbore storage effect is low which predicts the flow of liquid hydrocarbon into the well bore from the reservoir. Average pressure of the investigated zone has been estimated which is higher than the water column pressure. The higher average reservoir pressure also authenticates the presence of oil reservoir.Bangladesh J. Sci. Res. 29(1): 19-29, June-2016

Wellbore Storage and Skin Effects During the Transient Flow of Non-Newtonian Power-Law Fluids in Porous Media

1980 ◽  
Vol 20 (01) ◽  
pp. 25-38 ◽  
Author(s):  
Chi U. Ikoku ◽  
Henry J. Ramey
Keyword(s):  
Porous Media ◽  
Power Law ◽  
Transient Flow ◽  
Constant Pressure ◽  
Outer Boundary ◽  
Petroleum Reservoirs ◽  
Storage Effect ◽  
Well Test ◽  
Wellbore Storage ◽  
Power Law Fluids

Abstract A model recently presented by Ikoku and Ramey for non-Newtonian power-law flow in porous media was extended to flow in finite circular reservoirs. A constant flow rate was stipulated at the wellbore, and two boundary conditions were considered: no-flow outer boundary and constant-pressure outer boundary. The results were used to derive a new expression for the stabilization time for power-law flow in porous media.Wellbore storage and skin effects always distort the transient pressure behavior of wells in petroleum reservoirs. It is important to investigate the consequences of these phenomena and be able to interpret real well test information. This paper considers the effects of skin and wellbore storage on the transient flow of non-Newtonian power-law fluids in petroleum reservoirs. petroleum reservoirs. A new numerical wellbore storage simulator was used to study the effects of skin and wellbore storage during the transient flow of power-law fluids in infinitely large and finite circular reservoirs. Results are presented both in tabular form and as log-log graphs of dimensionless pressures vs dimensionless times. The log-log graphs may be used in a type-Curve matching procedure to analyze short-time well test data.The early period is dominated by wellbore storage effect. A new expression was obtained for the duration of wellbore storage effect when skin exists for infinitely large reservoirs. This criterion is not valid for finite circular reservoirs with no-flow outer boundary or constant-pressure outer boundary. Results indicate that there is no apparent end of wellbore storage effect for the no-flow outer boundary condition for the values of external radius presented. New relationships were derived for skin presented. New relationships were derived for skin factor and "effective well radius" for power-law flow. Introduction Many papers in the petroleum engineering, chemical engineering, and rheology literature have addressed the subject of non-Newtonian flow in porous media. These studies have represented non-Newtonian flow with power-law models. Most of the results are similar. The main differences in the final expressions lie in the type of power-law model used.In the basic papers on the transient flow of non-Newtonian power-law fluids in porous media, wellbore storage effect was not considered. Ikoku and Ramey and Odeh and Yang presented techniques for calculating the skin factor from injection well test data. However, wellbore storage and skin effects always distort the transient pressure behavior of wells in petroleum reservoirs. It is important to investigate the consequences of these phenomena to be able to interpret real well test information properly.The flow geometries of interest to petroleum engineers in well test analysis usually involve bounded reservoirs. In most cases, a constant flow rate is stipulated at the well along with one of these outer boundary conditions: no flow across the outer boundary, or constant pressure at the outer boundary. Reservoirs with rectangular and other polygonal shapes often are encountered. Transient polygonal shapes often are encountered. Transient pressure behavior for these shapes may be obtained pressure behavior for these shapes may be obtained by applying the principle of superposition in space to the solutions of the infinitely large reservoir cases.In this paper we seek solutions for constant-rate injection into finite circular reservoirs with no-flow and constant-pressure outer boundaries. SPEJ P. 25

Annulus Unloading Rates as Influenced by Wellbore Storage and Skin Effect

1972 ◽  
Vol 12 (05) ◽  
pp. 453-462 ◽  
Author(s):  
Henry J. Ramey ◽  
Ram G. Agarwal
Keyword(s):  
Test Data ◽  
Skin Effect ◽  
Transient Flow ◽  
Test Problems ◽  
Well Test ◽  
Pressure Drops ◽  
Wellbore Storage ◽  
Unloading Rate ◽  
Short Time ◽  
Storage Type

Abstract The modern trend in well testing (buildup or drawdown) bas been toward acquisition and analysis of short-time data. Pressure data early in a test are usually distorted by several factors that mask the conventional straight line. Some of the factors are wellbore storage and various skin effects such as those due to perforations, partial penetration, non-Darcy flow, or well stimulation effects. Recently, Agarwal et al. presented a fundamental study of the importance of wellbore storage with a skin effect to short-time transient flow. This paper further extends the concept of analyzing short-time well test data to include solutions of certain drillstem test problems and of cases wherein the storage constant, CD, undergoes an abrupt change from one constant value to another. An example of the latter case is change in storage type from compression to liquid level variations when tubinghead pressure drops to atmospheric Arks production. The purpose of the present paper is to: production. The purpose of the present paper is to:present tabular and graphical results for the sandface flow rate, qsf, and the annulus unloading rate, qa, as a fraction of the constant surface rate, q, andillustrate several practical well test situations that require such a solution. Results include a range of values of the storage constant, CD, and the skin effect, s, useful for well test problems. problems. Annulus unloading or storage bas been shown to be an important physical effect that often controls early well test behavior. As a result of this study, it appears that interpretations of short-time well test data can be made with a greater reliability, and solutions to other storage-dominated problems can be obtained easily. Techniques presented in this paper should enable the users to analyze certain short-time well test data that could otherwise be regarded as useless. Introduction In a recent paper, Agarwal et al. presented a study of the importance of wellbore storage with a skin effect to short-time transient flow. They also presented an analytical expression for the fraction presented an analytical expression for the fraction of the constant surface rate, q, produced from the annulus Although the rigorous solution (inversion integral) and long- and short-time approximate forms were discussed, neither tabular nor graphical results ofdpwD the annulus unloading rate, CD, were given.dtD It now appears that such solutions are useful in certain drillstem test problems and in cases wherein the storage constant, CD, changes during a well test. An example is change in storage type from compression to liquid level change when tubinghead pressure drops to atmospheric during production. pressure drops to atmospheric during production. The purpose of this study is to (1) present tabular and graphical results for the sandface flow rate and the annulus unloading rate and (2) illustrate several practical well test situations that require the practical well test situations that require the solutions. THE CLASSIC WELLBORE STORAGE PROBLEM The problem to be considered is one of flow of a slightly compressible fluid in an ideal radial flow system. SPEJ P. 453

scholarly journals A Mathematical Model for the Analysis of the Pressure Transient Response of Fluid Flow in Fractal Reservoir

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Jin-Zhou Zhao ◽  
Cui-Cui Sheng ◽  
Yong-Ming Li ◽  
Shun-Chu Li
Keyword(s):  
Fluid Flow ◽  
Boundary Conditions ◽  
Outer Boundary ◽  
Practical Significance ◽  
Storage Effect ◽  
Well Test ◽  
Type Curves ◽  
Skin Factor ◽  
Wellbore Storage ◽  
Wellbore Pressure

This study uses similar construction method of solution (SCMS) to solve mathematical models of fluid spherical flow in a fractal reservoir which can avoid the complicated mathematical deduction. The models are presented in three kinds of outer boundary conditions (infinite, constant pressure, and closed). The influence of wellbore storage effect, skin factor, and variable flow rate production is also involved in the inner boundary conditions. The analytical solutions are constructed in the Laplace space and presented in a pattern with one continued fraction—the similar structure of solution. The pattern can bring convenience to well test analysis programming. The mathematical beauty of fractal is that the infinite complexity is formed with relatively simple equations. So the relation of reservoir parameters (wellbore storage effect, the skin factor, fractal dimension, and conductivity index), the formation pressure, and the wellbore pressure can be learnt easily. Type curves of the wellbore pressure and pressure derivative are plotted and analyzed in real domain using the Stehfest numerical invention algorithm. The SCMS and type curves can interpret intuitively transient pressure response of fractal spherical flow reservoir. The results obtained in this study have both theoretical and practical significance in evaluating fluid flow in such a fractal reservoir and embody the convenience of the SCMS.

A Back Allocation Methodology to Estimate the Real-Time Flow and Assist Production Monitoring

2021 ◽  
Author(s):  
Gabriela Chaves ◽  
Danielle Monteiro ◽  
Virgilio José Martins Ferreira
Keyword(s):  
Real Time ◽  
Input Data ◽  
Oil Field ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Time Flow ◽  
Well Model ◽  
Operational Information ◽  
The Individual

Abstract Commingle production nodes are standard practice in the industry to combine multiple segments into one. This practice is adopted at the subsurface or surface to reduce costs, elements (e.g. pipes), and space. However, it leads to one problem: determine the rates of the single elements. This problem is recurrently solved in the platform scenario using the back allocation approach, where the total platform flowrate is used to obtain the individual wells’ flowrates. The wells’ flowrates are crucial to monitor, manage and make operational decisions in order to optimize field production. This work combined outflow (well and flowline) simulation, reservoir inflow, algorithms, and an optimization problem to calculate the wells’ flowrates and give a status about the current well state. Wells stated as unsuited indicates either the input data, the well model, or the well is behaving not as expected. The well status is valuable operational information that can be interpreted, for instance, to indicate the need for a new well testing, or as reliability rate for simulations run. The well flowrates are calculated considering three scenarios the probable, minimum and maximum. Real-time data is used as input data and production well test is used to tune and update well model and parameters routinely. The methodology was applied using a representative offshore oil field with 14 producing wells for two-years production time. The back allocation methodology showed robustness in all cases, labeling the wells properly, calculating the flowrates, and honoring the platform flowrate.

Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field

2021 ◽  
Author(s):  
Mohammed Ahmed Al-Janabi ◽  
Omar F. Al-Fatlawi ◽  
Dhifaf J. Sadiq ◽  
Haider Abdulmuhsin Mahmood ◽  
Mustafa Alaulddin Al-Juboori
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Middle Eastern ◽  
Optimization Technique ◽  
Injection Rate ◽  
Oil Field ◽  
Oil Fields ◽  
Reservoir Pressure ◽  
Artificial Lift ◽  
Gas Lift

Abstract Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorithm to tackle the challenging task of optimally allocating the gas lift injection rate through numerical modeling and simulation studies to maximize the oil production of a Middle Eastern oil field with 20 production wells with limited amount of gas to be injected. The key objective of this study is to assess the performance of the wells of the field after applying gas lift as an artificial lift method and applying the genetic algorithm as an optimization algorithm while comparing the results of the network to the case of artificially lifted wells by utilizing ESP pumps to the network and to have a more accurate view on the practicability of applying the gas lift optimization technique. The comparison is based on different measures and sensitivity studies, reservoir pressure, and water cut sensitivity analysis are applied to allow the assessment of the performance of the wells in the network throughout the life of the field. To have a full and insight view an economic study and comparison was applied in this study to estimate the benefits of applying the gas lift method and the GA optimization technique while comparing the results to the case of the ESP pumps and the case of naturally flowing wells. The gas lift technique proved to have the ability to enhance the production of the oil field and the optimization process showed quite an enhancement in the task of maximizing the oil production rate while using the same amount of gas to be injected in the each well, the sensitivity analysis showed that the gas lift method is comparable to the other artificial lift method and it have an upper hand in handling the reservoir pressure reduction, and economically CAPEX of the gas lift were calculated to be able to assess the time to reach a profitable income by comparing the results of OPEX of gas lift the technique showed a profitable income higher than the cases of naturally flowing wells and the ESP pumps lifted wells. Additionally, the paper illustrated the genetic algorithm (GA) optimization model in a way that allowed it to be followed as a guide for the task of optimizing the gas injection rate for a network with a large number of wells and limited amount of gas to be injected.

A Novel Well Test Data Analyzer and Process Optimizer Using Artificial Intelligence and Machine Learning Techniques

2021 ◽  
Author(s):  
Nagaraju Reddicharla ◽  
Subba Ramarao Rachapudi ◽  
Indra Utama ◽  
Furqan Ahmed Khan ◽  
Prabhker Reddy Vanam ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Real Time ◽  
Test Data ◽  
Oil Field ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Real Time Data ◽  
Well Tests

Abstract Well testing is one of the vital process as part of reservoir performance monitoring. As field matures with increase in number of well stock, testing becomes tedious job in terms of resources (MPFM and test separators) and this affect the production quota delivery. In addition, the test data validation and approval follow a business process that needs up to 10 days before to accept or reject the well tests. The volume of well tests conducted were almost 10,000 and out of them around 10 To 15 % of tests were rejected statistically per year. The objective of the paper is to develop a methodology to reduce well test rejections and timely raising the flag for operator intervention to recommence the well test. This case study was applied in a mature field, which is producing for 40 years that has good volume of historical well test data is available. This paper discusses the development of a data driven Well test data analyzer and Optimizer supported by artificial intelligence (AI) for wells being tested using MPFM in two staged approach. The motivating idea is to ingest historical, real-time data, well model performance curve and prescribe the quality of the well test data to provide flag to operator on real time. The ML prediction results helps testing operations and can reduce the test acceptance turnaround timing drastically from 10 days to hours. In Second layer, an unsupervised model with historical data is helping to identify the parameters that affecting for rejection of the well test example duration of testing, choke size, GOR etc. The outcome from the modeling will be incorporated in updating the well test procedure and testing Philosophy. This approach is being under evaluation stage in one of the asset in ADNOC Onshore. The results are expected to be reducing the well test rejection by at least 5 % that further optimize the resources required and improve the back allocation process. Furthermore, real time flagging of the test Quality will help in reduction of validation cycle from 10 days hours to improve the well testing cycle process. This methodology improves integrated reservoir management compliance of well testing requirements in asset where resources are limited. This methodology is envisioned to be integrated with full field digital oil field Implementation. This is a novel approach to apply machine learning and artificial intelligence application to well testing. It maximizes the utilization of real-time data for creating advisory system that improve test data quality monitoring and timely decision-making to reduce the well test rejection.

scholarly journals Production Optimization for Natural Flow and ESP Well A Case Study on Well NS-5 Mishrif Formation-Nasriya Oil Field

2020 ◽  
Vol 10 (2) ◽  
pp. 17-35
Author(s):  
Hamzah Amer Abdulameer ◽  
Dr. Sameera Hamd-Allah
Keyword(s):  
Production Rate ◽  
Production Optimization ◽  
Oil Field ◽  
Reservoir Pressure ◽  
Pump Frequency ◽  
Individual Parameter ◽  
Well Production ◽  
Well Design ◽  
Natural Flow ◽  
Reservoir Conditions

As the reservoir conditions are in continuous changing during its life, well production rateand its performance will change and it needs to re-model according to the current situationsand to keep the production rate as high as possible.Well productivity is affected by changing in reservoir pressure, water cut, tubing size andwellhead pressure. For electrical submersible pump (ESP), it will also affected by numberof stages and operating frequency.In general, the production rate increases when reservoir pressure increases and/or water cutdecreases. Also the flow rate increase when tubing size increases and/or wellhead pressuredecreases. For ESP well, production rate increases when number of stages is increasedand/or pump frequency is increased.In this study, a nodal analysis software was used to design one well with natural flow andother with ESP. Reservoir, fluid and well information are taken from actual data of Mishrifformation-Nasriya oil field/ NS-5 well. Well design steps and data required in the modelwill be displayed and the optimization sensitivity keys will be applied on the model todetermine the effect of each individual parameter or when it combined with another one.

scholarly journals Explicit Deconvolution of Well Test Data Dominated by Wellbore Storage

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
K. Razminia ◽  
A. Hashemi ◽  
A. Razminia ◽  
D. Baleanu
Keyword(s):  
Test Data ◽  
Material Balance ◽  
Early Time ◽  
Time Behavior ◽  
Well Test ◽  
Deconvolution Method ◽  
Pressure Data ◽  
Practical Applications ◽  
Wellbore Storage ◽  
Storage Effects

This paper addresses some methods for interpretation of oil and gas well test data distorted by wellbore storage effects. Using these techniques, we can deconvolve pressure and rate data from drawdown and buildup tests dominated by wellbore storage. Some of these methods have the advantage of deconvolving the pressure data without rate measurement. The two important methods that are applied in this study are an explicit deconvolution method and a modification of material balance deconvolution method. In cases with no rate measurements, we use a blind deconvolution method to restore the pressure response free of wellbore storage effects. Our techniques detect the afterflow/unloading rate function with explicit deconvolution of the observed pressure data. The presented techniques can unveil the early time behavior of a reservoir system masked by wellbore storage effects and thus provide powerful tools to improve pressure transient test interpretation. Each method has been validated using both synthetic data and field cases and each method should be considered valid for practical applications.

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