A Compositional Rescaled Exponential Model for Multiphase-Production-Performance Analysis of Boundary-Dominated Gas/Condensate Reservoirs

SPE Journal ◽  
2018 ◽  
Vol 24 (02) ◽  
pp. 618-646
Author(s):  
Ryan Will ◽  
Qian Sun ◽  
Luis F. Ayala
Keyword(s):  
Performance Analysis ◽  
Numerical Models ◽  
Compositional Analysis ◽  
Gas Condensate ◽  
Production Performance ◽  
Analytical Models ◽  
Reservoir Modeling ◽  
Well Performance ◽  
Reservoir Performance ◽  
Hydrocarbon Reservoir

Summary Hydrocarbon-reservoir-performance forecasting is an integral component of the resource-development chain and is typically accomplished using reservoir modeling, by means of either numerical or analytical methods. Although complex numerical models provide rigorous means of capturing and predicting reservoir behavior, reservoir engineers also rely on simpler analytical models to analyze well performance and estimate reserves when uncertainties exist. Arps (1945) empirically demonstrated that certain reservoirs might decline according to simple, exponential, hyperbolic, or harmonic relationships; such behavior, however, does not extend to more-complex scenarios, such as multiphase-reservoir depletion. Because of this limitation, an important research area for many years has been to transform the equations governing flow through porous media in such a way as to express complex reservoir performance in terms of closed analytical forms. In this work, we demonstrate that rigorous compositional analysis can be coupled with analytical well-performance estimations for reservoirs with complex fluid systems, and that the molar decline of individual hydrocarbon-fluid fractions can be expressed in terms of rescaled exponential equations for well-performance analysis. This work demonstrates that, by the introduction of a new partial-pseudopressure variable, it is possible to predict the decline behavior of individual fluid constituents of a variety of gas/condensate-reservoir systems characterized by widely varying richness and complex multiphase-flow scenarios. A new four-region-flow model is proposed and validated to implement gas/condensate-deliverability calculations at late times during variable-bottomhole-pressure (BHP) production. Five case studies are presented to support each of the model capabilities stated previously and to validate the use of liquid-analog rescaled exponentials for the prediction of production-decline behavior for each of the hydrocarbon species.

Production Performance Analysis of Volga-Ural Mature Waterflood with PRIME Diagnostic Metrics

2021 ◽  
Author(s):  
Artur Mihailovich Aslanyan ◽  
Bulat Galievich Ganiev ◽  
Azat Abuzarovich Lutfullin ◽  
Ildar Zufarovich Farkhutdinov ◽  
Marat Yurievich Garnyshev ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Production Performance ◽  
Diagnostic Tools ◽  
Practical Case ◽  
Well Performance ◽  
Summary Table ◽  
Main Challenge ◽  
Production History ◽  
Infill Drilling ◽  
Production Trend

Abstract The paper presents a practical case of production performance analysis at one of the mature waterflood oil fields located at the Volga-Ural oil basin with a large number of wells. It is a big challenge to analyse such a large production history and requires a systematic approach. The main production complication is quite common for mature waterflood projects and includes non-uniform sweep, complicated by thief injection and thief water production. The main challenge is to locate the misperforming wells and address their complications. With the particular asset, the conventional single production analysis techniques (oil production trend, watercut trend, reservoir and bottom-hole pressure trend, productivity trend, conventional pressure build-up surveys and production logging) in the vast majority of cases were not capable of qualifying the well performance and assessing of remaining reserves status. The performance analysis of such an asset should be enhanced with new diagnostic tools and modern methods of data integration. The current study has made a choice in favor of using a PRIME analysis which is multi-parametric analytical workflow based on a set of conventional and non-conventional diagnostic metrics. The most effective diagnostics in this study have happened to be those are based on 3D dynamic micro-models, which are auto-generated from the reservoir data logs. PRIME also provided useful insights on well performance, formation properties and the current conditions of drained reserves which helped to select the candidates for infill drilling, pressure maintenance, workovers, production target adjustments and additional surveillance. The paper illustrates the entire PRIME workflow, starting from the top-level field data analysis, all the way to generating a summary table containing well diagnostics, justifications and recommendations.

scholarly journals A production-based model for a fractured well in unconventional reservoirs

2020 ◽  
Author(s):  
Shaibu Mohammed ◽  
Prosper Anumah1 ◽  
Justice Sarkodie-kyeremeh ◽  
Emmanuel Acheaw
Keyword(s):  
Power Law ◽  
Numerical Models ◽  
Transient State ◽  
Production Performance ◽  
Unconventional Reservoirs ◽  
Well Performance ◽  
Type Curves ◽  
Stretched Exponential ◽  
Proposed Model ◽  
Fractured Well

Due to the depletion of conventional reservoirs and the high demand of energy, unconventional reservoirs will be relied on to supply the world’s energy for the foreseeable future. Unfortunately, modelling and analysis of these reservoirs have been very challenging because of their complex storage and flow mechanisms. Although analytical, semi-analytical and numerical models have been proposed, these models rely on simplifying assumptions and require several input parameters. In this paper, a production-based model is proposed to analyze and predict a fractured-well performance in unconventional reservoirs. The model assumes a power law with a stretched exponential cut-off. While the power-law term governs the transient-state period, the stretched exponential term, which is a superposition of exponential decays, governs the boundary-dominated flow period. As a result, the model is capable of matching both the transient state and boundary-dominated flow portions of the data. The model has been validated with a numerical data and applied to several field data; in addition, the model has been used to estimate P10, P50 and P90 values, as well as to develop P10, P50 and P90 type curves for the Barnett shale. These type curves will be useful for production forecasting of new wells in the field or analogue fields. Results of the model have been compared with existing models. The findings show that the proposed model yields relatively good reserve estimates, and predicts the future production performance of unconventional reservoirs not only during the transient-state period, but also the boundary-dominated flow period. The proposed model may contribute to the ongoing efforts to improve the analysis and forecasting of fractured-well performance in unconventional reservoirs.

Improving reservoir performance using intelligent well completion sensors combined with surface wet-gas flow measurement

2012 ◽  
Vol 52 (1) ◽  
pp. 181
Author(s):  
Nematollah Tarom ◽  
Mofazzal Hossain
Keyword(s):  
Data Acquisition ◽  
Gas Flow ◽  
Reservoir Management ◽  
Production Performance ◽  
Well Performance ◽  
Reservoir Performance ◽  
Well Completion ◽  
Wet Gas ◽  
Wellbore Pressure ◽  
Reservoir Conditions

Reservoir performance, in addition to day-to-day well performance, needs to be evaluated during the life of a well. The production logging tool (PLT) is conventionally designed to provide a full set of data measurements in producing wells to evaluate well and reservoir performance. Depending on the well conditions and location, running conventional PLTs may be difficult, impossible or expensive. Therefore, an alternative approach that can be applied in lieu of PLT operations—to obtain information similar to PLTs for better reservoir management—and that can optimise reservoir production performance is desireable. Data acquisition techniques such as downhole pressure/temperature gauges, fibre optic sensors at reservoir conditions and wet-gas flow meters at the surface have been considered as a viable alternative. Such data acquisition techniques help to increase flexibility in the field development and reservoir management of problematic wells with well completion technologies such as multi-lateral, horizontal and artificial lift. This study focused on the development of an alternative method of analysing problem well data on the basis of downhole pressure and temperature data collected at reservoir conditions. The proposed model has been based on the Joule-Thomson effect and radial heat and fluid flow equations to solve the transient wellbore pressure and temperature equations. It is expected this model can be used to analyse intelligent wells completed with downhole pressure and temperature sensors, and facilitate the monitoring of wells and reservoir performance without any PLT operation, especially for complex fields.

scholarly journals Improved Steamflood Analytical Model

2007 ◽  
Vol 10 (06) ◽  
pp. 638-643
Author(s):  
Suandy Chandra ◽  
Daulat Debataraja Mamora
Keyword(s):  
Analytical Model ◽  
Performance Prediction ◽  
Numerical Models ◽  
Production Performance ◽  
Analytical Models ◽  
Rock Properties ◽  
Oil Viscosity ◽  
Modified Model ◽  
Jones Model ◽  
Simulation Results

Summary The Jones (1981) steamflood model incorporates oil displacement by steam as described by Myhill and Stegemeier (1978), and a three-component capture factor based on empirical correlations. The main drawback of the model, however, is the unsatisfactory prediction of the oil production peak: It is usually significantly lower than the observed value. Our study focuses on improving this aspect of the Jones model. In our study, we simulated the production performance of a five-spot-steamflood-pattern unit and compared the results against those based on the Jones model (1981). To obtain a satisfactory match between simulation and Jones-analytical-model results, at the start and height of the production peak, the following refinements to the Jones model were necessary. First, the dimensionless steam-zone size AcD was modified to account for the decrease in oil viscosity during steamflood and its dependence on the steam injection rate. Second, the dimensionless volume of displaced oil produced VoD was modified from its square-root format to an exponential form. The modified model gave very satisfactory results for production performance for up to 20 years of simulated steamflood, compared to the original Jones model. Engineers will find the modified model an improved and useful tool for the prediction of steamflood-production performance. Introduction Steamflooding is a major enhanced-oil recovery (EOR) process applied to heavy oil reservoirs. A steamflood typically proceeds through four development phases: reservoir screening, pilot tests, fieldwide implementation, and reservoir management (Hong 1994). Steamflood-performance prediction is essential to provide information for the proper execution of each development phase. Three mathematical models (statistical, numerical, and analytical models) are often used to predict steamflood performance. Statistical models are based on the historical data of steamflood performance from other reservoirs which have similar oil and rock properties. A statistical model, however, does not include all the flow parameters, and thus may be inaccurate for a particular reservoir. Numerical models usually require a large amount of data input with lengthy calculations using computers; and they are usually CPU-, manpower- and time-consuming and also expensive. They may be extremely comprehensive and better serve as tools for research or advanced reservoir analysis. Meanwhile, analytical models are more economical, but at the expense of accuracy and flexibility. They serve as tools for engineering screening of possible reservoir candidates for field testing (Hong 1994). For many years, attempts have been made to provide analytical models for steamflood-production-performance prediction (Marx and Langenheim 1959; Boberg 1966; Mandl and Volek 1969; Neuman 1975; Myhill and Stegemeier 1978; Gomaa 1980; Jones 1981; van Lookeren 1977; Farouq Ali 1970; Miller and Leung 1985; Rhee et al. 1978; Aydelotte et al. 1982). None of these analytical models gives a comparison with simulation results. Miller and Leung (1985) presented comparison between their analytical model and simulation results for cumulative production vs time, but the comparison for production rate vs time is not available.

scholarly journals An integrated workflow to perform reservoir and completion parametric study on a shale gas reservoir

2020 ◽  
Vol 10 (4) ◽  
pp. 1497-1510
Author(s):  
Mohamed Mahmoud ◽  
Ahmed Aleid ◽  
Abdulwahab Ali ◽  
Muhammad Shahzad Kamal
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Production Performance ◽  
Analytical Models ◽  
Well Performance ◽  
Short Term ◽  
Gas Reservoirs ◽  
Shale Gas Reservoirs ◽  
The Impact

AbstractThe main objectives of this paper are to assess the long-term and short-term production based on both reservoir parameters and completion parameters of shale gas reservoirs. The effects of the reservoir parameters (permeability and the initial reservoir pressure) and completion parameters (fracture geometry, stimulated reservoir volume, etc.) on the short-term and long-term production of shale gas reservoirs were investigated. The currently used approach relies mainly on the decline curve analysis or analogs from a similar shale play to forecast the gas production from shale gas reservoirs. Both these approaches are not satisfactory because they are calibrated on short production history and do not assess the impact of uncertainty in reservoir and well data. For the first time, this study integrates initial production analysis, probabilistic evaluation, and sensitivity analysis to develop a robust workflow that will help in designing a sustainable production from shale gas plays. The reservoir and completion parameters were collected from different available resources, and the probability distributions of gathered uncertain data were defined. Then analytical models were used to forecast the production. Two well evaluation results are presented in this paper. Based on the results, completion parameters affected the short-term and long-term production, while the reservoir parameters controlled the long-term production. Long-term well performance was mainly controlled by the fracture half-length and fracture height, whereas other completion and reservoir parameters have an insignificant effect. Stimulation treatment design defines the initial well performance, while well placement decision defines well long-term performance. The findings of this study would help in better understanding the production performance of shale gas reservoirs, maximizing production by selecting effective completion parameters and considering the governing reservoir parameters. Moreover, it would help in accomplishing more effective stimulation treatments and define the potentiality of the basin.

THE ROLE OF RESERVOIR SIMULATION IN THE DEVELOPMENT OF THE CHALLIS AND CASSINI FIELDS

1990 ◽  
Vol 30 (1) ◽  
pp. 212
Author(s):  
I.G.D. Gorman
Keyword(s):  
Water Injection ◽  
Oil Field ◽  
Production Performance ◽  
Analytical Models ◽  
Production Test ◽  
Well Performance ◽  
Initial Development ◽  
Field Development ◽  
Production Wells ◽  
Interference Test

The Challis oil field development was approved in 1987 with marginal reserves (for an isolated offshore project) of 22 MMbbl. The initial development envisaged three subsea production wells connected via a riser to a floating production facility with one water injector also being required to maximise recovery. However, due to additional potential in the vicinity of the field, the production system was designed to accommodate up to 10 production/injection wells.Further appraisal in 1988/1989 doubled the reserves to 43 MMbbl and increased the number of initial production wells to seven from five reservoirs. The appraisal results also confirmed earlier concerns as to the structural complexity of the field. Analytical interpretations of the production tests performed on the wells could not be fully reconciled with the available well log, core and seismic data. Furthermore, the analytical models developed from these interpretations could not fully match the test results.Reservoir simulation was used to resolve, where possible, the discrepancies. Individual reservoir models were calibrated with the production test results and used to quantify the major uncertainties and their potential impact on production performance. The simulation results indicated that water injection may not be required. However, the degree of internal reservoir communication and the extent of the expected aquifer support were identified as the two principal unknowns.Production policy and monitoring procedures were structured to resolve these uncertainties as quickly as possible during the production start-up phase. Comparative forecasts of expected performance were developed for each reservoir with various levels of aquifer support. A surface controlled interference test was designed to investigate the extent of internal reservoir communication in the main reservoir.The success of the interference test and the results of the early well performance have confirmed the simulation predictions. Simulation modelling was successful in quantifying the range of expected pressure response (to production) for each reservoir and was able to quickly confirm the degree of pressure support present in each reservoir.

A Generalized Compositional Approach for Reservoir Simulation

1983 ◽  
Vol 23 (05) ◽  
pp. 727-742 ◽  
Author(s):  
Larry C. Young ◽  
Robert E. Stephenson
Keyword(s):  
Enhanced Recovery ◽  
Gas Condensate ◽  
Reservoir Modeling ◽  
Pressure Equation ◽  
Compositional Modeling ◽  
Fluid Property ◽  
Black Oil ◽  
Fluid Properties ◽  
Newton Raphson ◽  
Raphson Method

A procedure for solving compositional model equations is described. The procedure is based on the Newton Raphson iteration method. The equations and unknowns in the algorithm are ordered in such a way that different fluid property correlations can be accommodated leadily. Three different correlations have been implemented with the method. These include simplified correlations as well as a Redlich-Kwong equation of state (EOS). The example problems considered area conventional waterflood problem,displacement of oil by CO, andthe displacement of a gas condensate by nitrogen. These examples illustrate the utility of the different fluid-property correlations. The computing times reported are at least as low as for other methods that are specialized for a narrower class of problems. Introduction Black-oil models are used to study conventional recovery techniques in reservoirs for which fluid properties can be expressed as a function of pressure and bubble-point pressure. Compositional models are used when either the pressure. Compositional models are used when either the in-place or injected fluid causes fluid properties to be dependent on composition also. Examples of problems generally requiring compositional models are primary production or injection processes (such as primary production or injection processes (such as nitrogen injection) into gas condensate and volatile oil reservoirs and (2) enhanced recovery from oil reservoirs by CO or enriched gas injection. With deeper drilling, the frequency of gas condensate and volatile oil reservoir discoveries is increasing. The drive to increase domestic oil production has increased the importance of enhanced recovery by gas injection. These two factors suggest an increased need for compositional reservoir modeling. Conventional reservoir modeling is also likely to remain important for some time. In the past, two separate simulators have been developed and maintained for studying these two classes of problems. This result was dictated by the fact that compositional models have generally required substantially greater computing time than black-oil models. This paper describes a compositional modeling approach paper describes a compositional modeling approach useful for simulating both black-oil and compositional problems. The approach is based on the use of explicit problems. The approach is based on the use of explicit flow coefficients. For compositional modeling, two basic methods of solution have been proposed. We call these methods "Newton-Raphson" and "non-Newton-Raphson" methods. These methods differ in the manner in which a pressure equation is formed. In the Newton-Raphson method the iterative technique specifies how the pressure equation is formed. In the non-Newton-Raphson method, the composition dependence of certain ten-ns is neglected to form the pressure equation. With the non-Newton-Raphson pressure equation. With the non-Newton-Raphson methods, three to eight iterations have been reported per time step. Our experience with the Newton-Raphson method indicates that one to three iterations per tune step normally is sufficient. In the present study a Newton-Raphson iteration sequence is used. The calculations are organized in a manner which is both efficient and for which different fluid property descriptions can be accommodated readily. Early compositional simulators were based on K-values that were expressed as a function of pressure and convergence pressure. A number of potential difficulties are inherent in this approach. More recently, cubic equations of state such as the Redlich-Kwong, or Peng-Robinson appear to be more popular for the correlation Peng-Robinson appear to be more popular for the correlation of fluid properties. SPEJ p. 727

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