The Inversion of Formation Parameters after Volume Fracturing

2014 ◽  
Vol 548-549 ◽  
pp. 428-430
Author(s):  
Jiao Peng ◽  
Xin Min Shao ◽  
De Sheng Zhou
Keyword(s):  
Mathematical Formulation ◽  
Oil Field ◽  
Finite Conductivity ◽  
Tight Oil ◽  
Well Testing ◽  
Method Of Images ◽  
Fracture Conductivity ◽  
Volume Fracturing ◽  
Flow Boundaries ◽  
Solution Methodology

Volume fracturing is the key technology that has made the development of tight oil formations economical. Well testing is often used to obtain formation parameters in oil field after volume fracturing in tight oil formations, which is time-consuming and accuracy is low. Based on a new analytical solution methodology, this paper presents a simple and efficient approach by matching the production data to obtain formation parameters, just like formation permeability, fracture conductivity, dimensionless conductivity, propped length and so on. The numerical solution is applicable for finite-conductivity vertical fractures in rectangular shaped reservoirs. The mathematical formulation is based on the method of images with no flow boundaries for symmetrical patterns.

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.

Unlocking Idle Production in an Offshore Sandstone Oil Field With Gas Hydrate Issues

2021 ◽  
Author(s):  
Babalola Daramola
Keyword(s):  
Gas Hydrate ◽  
Oil Production ◽  
Oil Field ◽  
Third Party ◽  
Flow Assurance ◽  
Well Testing ◽  
Production Wells ◽  
Oil Flow ◽  
Offshore Oil ◽  
Production Losses

Abstract This publication presents how an oil asset unlocked idle production after numerous production upsets and a gas hydrate blockage. It also uses economics to justify facilities enhancement projects for flow assurance. Field F is an offshore oil field with eight subsea wells tied back to a third party FPSO vessel. Field F was shut down for turnaround maintenance in 2015. After the field was brought back online, one of the production wells (F5) failed to flow. An evaluation of the reservoir, well, and facilities data suggested that there was a gas hydrate blockage in the subsea pipeline between the well head and the FPSO vessel. A subsea intervention vessel was then hired to execute a pipeline clean-out operation, which removed the gas hydrate, and restored F5 well oil production. To minimise oil production losses due to flow assurance issues, the asset team evaluated the viability of installing a test pipeline and a second methanol umbilical as facilities enhancement projects. The pipeline clean-out operation delivered 5400 barrels of oil per day production to the asset. The feasibility study suggested that installing a second methanol umbilical and a test pipeline are economically attractive. It is recommended that the new methanol umbilical is installed to guarantee oil flow from F5 and future infill production wells. The test pipeline can be used to clean up new wells, to induce low pressure wells, and for well testing, well sampling, water salinity evaluation, tracer evaluation, and production optimisation. This paper presents production upset diagnosis and remediation steps actioned in a producing oil field, and aids the justification of methanol umbilical capacity upgrade and test pipeline installations as facilities enhancement projects. It also indicates that gas hydrate blockage can be prevented by providing adequate methanol umbilical capacity for timely dosing of oil production wells.

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 Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology that Combines the Salp Swarm Algorithm and the Successive Approximation Method

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2837
Author(s):  
Andrés Alfonso Rosales Muñoz ◽  
Luis Fernando Grisales-Noreña ◽  
Jhon Montano ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Distributed Generation ◽  
Direct Current ◽  
Mathematical Formulation ◽  
Average Power ◽  
Power Losses ◽  
Salp Swarm Algorithm ◽  
Test Systems ◽  
Distributed Generators ◽  
Optimal Power ◽  
Solution Methodology

This paper addresses the Optimal Power Flow (OPF) problem in Direct Current (DC) networks by considering the integration of Distributed Generators (DGs). In order to model said problem, this study employs a mathematical formulation that has, as the objective function, the reduction in power losses associated with energy transport and that considers the set of constraints that compose DC networks in an environment of distributed generation. To solve this mathematical formulation, a master–slave methodology that combines the Salp Swarm Algorithm (SSA) and the Successive Approximations (SA) method was used here. The effectiveness, repeatability, and robustness of the proposed solution methodology was validated using two test systems (the 21- and 69-node systems), five other optimization methods reported in the specialized literature, and three different penetration levels of distributed generation: 20%, 40%, and 60% of the power provided by the slack node in the test systems in an environment with no DGs (base case). All simulations were executed 100 times for each solution methodology in the different test scenarios. The purpose of this was to evaluate the repeatability of the solutions provided by each technique by analyzing their minimum and average power losses and required processing times. The results show that the proposed solution methodology achieved the best trade-off between (minimum and average) power loss reduction and processing time for networks of any size.

Effect of Non-Darcy Flow on the Constant-Pressure Production of Fractured Wells

1981 ◽  
Vol 21 (03) ◽  
pp. 390-400 ◽  
Author(s):  
K.H. Guppy ◽  
Heber Cinco-Ley ◽  
Henry J. Ramey
Keyword(s):  
Constant Pressure ◽  
Darcy Flow ◽  
Flow In Porous Media ◽  
Graphical Form ◽  
Finite Conductivity ◽  
Fracture Conductivity ◽  
Type Curves ◽  
Pressure Behavior ◽  
Apparent Conductivity ◽  
Constant Rate

Abstract In many low-permeability gas reservoirs, producing a well at constant rate is very difficult or, in many cases, impossible. Constant-pressure production is much easier to attain and more realistic in practice. This is seen when production occurs into a constant-pressure separator or during the reservoir depletion phase, when the rate-decline period occurs. Geothermal reservoirs, which produce fluids that drive backpressure turbines, and open-well production both incorporate the constant-pressure behavior. For finite-conductivity vertically fractured systems, solutions for the constant-pressure case have been presented in the literature. In many high-flow-rate wells, however, these solutions may not be useful since high velocities are attained in the fracture, which results in non-Darcy effects within the fracture. In this study, the effects of non-Darcy flow within the fracture are investigated. Unlike the constant-rate case, it was found that the fracture conductivity does not have a constant apparent conductivity but rather an apparent conductivity that varies with time. Semianalytical solutions as well as graphical solutions in the form of type curves are presented to illustrate this effect. An example is presented for analyzing rate data by using both solutions for Darcy and non-Darcy flow within the fracture. This example relies on good reservoir permeability from prefracture data to predict the non-Darcy effect accurately. Introduction To fully analyze the effects of constant-bottomhole-pressure production of hydraulically fractured wells, it is necessary that we understand the pressure behavior of finite-conductivity fracture systems producing at constant rate as well as the effects of non-Darcy flow on gas flow in porous media. Probably one of the most significant contributions in the transient pressure analysis theory for fractured wells was made by Gringarten et al.1,2 In the 1974 paper,2 general solutions were made for infinite-conductivity fractures. Cinco et al.3 found a more general solution for the case of finite-conductivity fractures and further extended this analysis in 1978 to present a graphical technique to estimate fracture conductivity.4 For the case of constant pressure at the wellbore, solutions were presented in graphical form by Agarwal et al.5 In his paper, a graph of log (1/qD) vs. log (tDxf) can be used to determine the conductivity of the fracture by using type-curve matching. Although such a contribution is of great interest, unique solutions are difficult to obtain. More recently, Guppy et al.6 showed that the Agarwal et al. solutions may be in error and presented new type curves for the solution to the constant-pressure case assuming Darcy flow in the fracture. That paper developed analytical solutions which can be applied directly to field data so as to calculate the fracture permeability-width (kfbf) product.

The Performance Evaluation of Old Well after SRV in Ordos Basin Tight Oil Reservoir

2014 ◽  
Author(s):  
H.. Wang ◽  
X.. Liao ◽  
H.. Ye ◽  
X.. Zhao ◽  
C.. Liao ◽  
...  
Keyword(s):  
Evaluation Method ◽  
Ordos Basin ◽  
Fracture Network ◽  
Water Flooding ◽  
Tight Oil ◽  
Oil Reservoir ◽  
Well Test ◽  
Stimulated Reservoir Volume ◽  
Tight Oil Reservoir ◽  
Volume Fracturing

Abstract The technology of Stimulated reservoir volume (SRV) has been the key technology for unconventional reservoir development, it can create fracture network in formation and increase the contact area between fracture surface and matrix, thus realizing the three-dimensional stimulation and enhancing single well productivity and ultimate recovery. In China, the Ordos Basin contains large areas of tight oil reservoir with the porosity of 2~12 % and permeability of 0.01~1 mD. The most used development mode is conventional fracturing and water flooding, which is different from the natural depletion mode in oversea, but the development effect is still unfavorable. The idea of SRV is proposed in nearly two years in Changqing Oilfield. SRV measures are implemented in some old wells in tight oil formation. It is a significant problem that should be solved urgently about how to evaluate the volume fracturing effect. Based on the real cases of old wells with SRV measures, the microseismic monitoring is used to analyze the scale of formation stimulation and the complexity of fracture network after volume fracturing; the numerical well test and production data analysis (PDA) are selected to explain the well test data, to analyze the dynamic data, and to compare the changes of formation parameters, fluid parameters and plane streamlines before and after volume fracturing; then the interpretation results of well test with the dynamic of oil and water wells are combined to evaluate the stimulation results of old wells after SRV. This paper has presented a set of screening criteria and an evaluation method of fracturing effect for old well with SRV in tight oil reservoir. It will be helpful to the selection of candidate well and volume fracturing operation in Ordos Basin tight oil reservoir. It should be noted that the evaluation method mentioned in the paper can be expanded to volume stimulation effect evaluation in other unconventional reservoirs, such as tight gas, shale gas and so on.

Unique Fall Off Signatures for Stage Fracture Characterization, Actual Field Cases

2021 ◽  
Author(s):  
Ahmed Farid Ibrahim ◽  
Mazher Ibrahim ◽  
Matt Sinkey ◽  
Thomas Johnston ◽  
Wes Johnson
Keyword(s):  
Flow Regime ◽  
Surface Area ◽  
Fiber Optics ◽  
In Situ Stress ◽  
Tensile Fracture ◽  
Finite Conductivity ◽  
Well Performance ◽  
Fracture Geometry ◽  
Fracture Conductivity ◽  
Diagnostic Plots

Abstract Multistage hydraulic fracturing is the common stimulation technique for shale formations. The treatment design, formation in-situ stress, and reservoir heterogeneity govern the fracture network propagation. Different techniques have been used to evaluate the fracture geometry and the completion efficiency including Chemical Tracers, Microseismic, Fiber Optics, and Production Logs. Most of these methods are post-fracture as well as time and cost intensive processes. The current study presents the use of fall-off data during and after stage fracturing to characterize producing surface area, permeability, and fracture conductivity. Shut-in data (15-30 minutes) was collected after each stage was completed. The fall-off data was processed first to remove the noise and water hammer effects. Log-Log derivative diagnostic plots were used to define the flow regime and the data were then matched with an analytical model to calculate producing surface area, permeability, and fracture conductivity. Diagnostic plots showed a unique signature of flow regimes. A long period of a spherical flow regime with negative half-slope was observed as an indication for limited entry flow either vertically or horizontally. A positive half-slope derivative represents a linear flow regime in an infinitely conductive tensile fracture. The quarter-slope derivative was observed in a bilinear flow regime that represents a finite conductivity fracture system. An extended radial flow regime was observed with zero slope derivative which represents a highly shear fractured network around the wellbore. For a long fall-off period, formation recharge may appear with a slope between unit and 1.5 slopes derivative, especially in over-pressured dry gas reservoirs. Analyzing fall-off data after stages are completed provides a free and real-time investigation method to estimate the fracture geometry and a measure of completion efficiency. Knowing the stage properties allows the reservoir engineer to build a simulation model to forecast the well performance and improve the well spacing.

Optimized Clay Control Fracturing Fluid Used in a Highly Water-Sensitive Tight Oil Reservoir Hydraulic Fracturing Application in Xinjiang Oil Field: Case Study

2021 ◽  
Author(s):  
Xinjun Mao ◽  
Chaofeng Chen ◽  
Renzhong Gan ◽  
Shubo Zhou ◽  
Zichao Wang ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
Recovery Rate ◽  
Oil Field ◽  
National Standard ◽  
Working Fluid ◽  
Tight Oil ◽  
Fracturing Fluid ◽  
Core Flow ◽  
Velocity Sensitivity ◽  
Highly Sensitive

Abstract The candidate wells are tight oil wells and most of the wells in the area have a low recovery rate of fracturing fluid after fracturing treatment. The lithology is glutenite with weak cementation and a high sensitivity tendency. This paper presents the process of sensitivity evaluation and fracturing fluid evaluation. Also, this paper introduces a customized and optimized clay control fracturing fluid wells in a highly sensitive reservoir. Per local national standard, traditional methods of swelling test (ST) and x-ray diffraction (XRD) were employed for qualitative formation cutting analysis. An innovative trial was then developed to evaluate cores quantitatively by water sensitivity. A clay stabilizer was then chosen to be used for the highly sensitive cores and regain permeability testing of the broken fracturing fluid was performed. Based on the analysis and evaluation, a customized treatment design was initiated for the hydraulic fracturing treatment. The qualitative evaluation showed the rock is highly water sensitive and the cores easily collapse because of weak cementation. No flow could be established during traditional core flow tests with brine. The newly developed method used kerosene as the working fluid to prevent the cores from contact with water or brine. The core flow tests resulted in a velocity sensitivity damage rate of 92%, which is considered as highly velocity sensitive. Accordingly, a special clay stabilizer was chosen to be used in the fracturing fluid and the permeability damage of the broken fracturing fluid is only 26.9%(Table 16). Field results have shown that the fracturing fluid recovery rate in treated wells is higher than the area average level and treated wells have significant oil production increase. The innovative clay control fracturing fluid and its field application reduces the influence of water and velocity sensitivity. The customized treatment with special clay stabilizer helps increase the recovery rate of fracturing fluid in reservoirs with severe clay stability and weak cementation issues.

New Analytical Approach to Operational Assessment of Fractured Well Productivity with Variable Permeability

2021 ◽  
Author(s):  
Evgeniy Viktorovich Yudin ◽  
George Aleksandrovich Piotrovskiy ◽  
Maria Vladimirovna Petrova ◽  
Alexey Petrovich Roshchektaev ◽  
Nikita Vladislavovich Shtrobel
Keyword(s):  
Hydraulic Fracturing ◽  
Hydraulic Fracture ◽  
Free Parameter ◽  
Numerical Solutions ◽  
Analytical Models ◽  
Productivity Index ◽  
Finite Conductivity ◽  
Well Productivity ◽  
Fracture Conductivity ◽  
Variable Permeability

Abstract Requirements of targeted optimization are imposed on the hydraulic fracturing operations carried out in the conditions of borderline economic efficiency of fields taking into account geological and technological features. Consequently, the development of new analytical tools foranalyzing and planning the productivity of fractured wells, taking into account the structuralfeatures of the productive reservoir and inhomogeneous distribution of the fracture conductivity, is becoming highly relevant. The paper proposes a new approach of assessing the vertical hydraulic fracture productivityin a rectangular reservoir in a pseudo-steady state, based on reservoir resistivity concept described in the papers of Meyer et al. However, there is a free parameter in the case of modeling the productivity of a hydraulic fracture by the concept. The parameter describes the distribution of the inflow along the plane of the fracture. This paper presents a systematic approach to determining of the parameter. The resulting model allows to conduct an assessment of the influence of various complications in the fracture on the productivity index. During the research a method of determining the free parameter was developed,it was based on the obtained dependence of the inflow distribution on the coordinate along the fracture of finite conductivity. The methodology allowed to refine existent analytical solution of the Meyer et al. model, which, in turn, allowed to assess the influence of different fracture damages in the hydraulic fracture on the productivity index of the well. The work includes the cases of the presence of fracture damages at the beginning and at the end of the fracture. A hydraulic fracture model was built for each of the types of damages, it was based on the developed method, and also the solution of dimensionless productivity ratio was received. The results of the obtained solution were confirmed by comparison with the numerical solutions of commercial simulators and analytical models available in the literature. The advantage of the methodology is the resulting formulas for well productivity are relatively simple, even for exotic cases ofvariable conductivity fractures. The approaches and algorithms described in the paper assume the calculation of the productivity of a hydraulic fracture with variable conductivity and the presence of other complicatingfactors.The methodology of the paper can be used for analysis and diagnosis problems with formation hydraulic fracturing. The efficiency of the calculations allows using the presented methodology to solve inverse problems of determining the efficiency of the hydraulic fracturing operation.

Sign in / Sign up

Export Citation Format

Share Document