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Gas-condensate reservoirs exhibit complex multi-phase flow behavior below saturation pressures resulting from compositional variations. Below saturation pressure, condensate starts dropping-out within the reservoir and eventually develops a bank in the near wellbore region; effectively reducing the relative permeability to gas flow. As a result, production of main phase (gas) decreases with development of this bank while condensate is left behind in the reservoir. Since, reserves estimation is a part of the development plans of all fields, it is important to account for condensate drop-out while deriving a condensate recovery factor during the initial stage of the life of a reservoir. Otherwise a high condensate recovery factor (if assumed equal to or close to that of gas phase) might result in unrealistic optimistic cash flow projections. Given the importance of condensate recovery factor estimation, a data driven analytical method has been developed and will be discussed in detail in this paper; while overcoming the limitation of available data for green fields. An analytical methodology has been developed for calculation of condensate recovery factor in gas condensate reservoirs in the absence of a constant volume depletion (CVD) study laboratory report. The method uses either a linear or a non-linear correlation-based relationship between condensate drop-out and pressure. This enables derivation of an equation for calculation of condensate recovery factor while incorporating critical parameters such as dew point pressure, initial and abandonment pressures and condensate gas ratios (CGRs) at initial and abandonment conditions. A stepwise procedure will be described to derive all these parameters with limited available data in the early stages of the life of reservoir. The methodology adopted was applied to more than 30 green and brown gas condensate fields with varying CGR's. For a few mature fields, results derived from the proposed methodology were compared with recovery factors estimated from numerical simulation models. Results of both approaches appeared to be in a good agreement with an accuracy of +/−10%. As expected, recovery factors derived assuming a simple linear decline of CGR with pressure were less accurate than those calculated using a non-linear correlation-based decline of CGR with pressure. For richer gas condensate fields with high compressibility factors, the z-factor was incorporated with pressure in the form of P/z, which resulted in a more accurate estimation of recovery factors. A comparison has been made where recovery factors are estimated from the described approach and the other reference approaches; and conclusions drawn from these comparisons are discussed. Various approaches have been used historically for condensate recovery factor estimation while relying heavily on a good amount of data available. A simple analytical approach has been discussed which mitigates the impact of poor data availability especially in green fields and yet can yield useable condensate recovery factor calculations. This enables better reserve estimation of condensates in gas condensate reservoirs in early stages of life of reservoirs, while leading to efficient and realistic field development plans in futures.

The reservoir management team is often facing a standardization challenge during audit and screening of inactive wells, especially if this task involves multiple mature oil reservoirs or fields. Such a well candidate screening process is normally required to select candidates for revival as well as plug and abandonment (P&A) candidates. Shut-in wells across different fields may be sharing common issues such as pressure depletion, liquid loading, and high water cut, however, the severity of well-related problems varies from one field to the other. This is in addition to the variation of wellbore mechanical issues such as well-bore integrity, wellbore accessibility, and others. This paper aims to demonstrate a workflow to provide a quantitative ranking of wells. It can be used to standardize an audit process during multi-reservoir or multi-field inactive-well candidate screening study. The standardization process was addressed by developing a tool that registers the shut-in well ranking upon completing the well potential and risk assessment process. Well level petroleum engineering and production data analysis such as decline curve analysis, nodal analysis and well modeling are performed to estimate the remaining well potential. Subsequently, to enable a comparison across different fields, behind pipe well potential was normalized using multi-field parameters. The audit process followed with well workover risking based on ease of workover intervention including workover options such as water shut off, remedial wellbore integrity work, stimulation and others where it also draws on local knowledge for well risk calculation. The approach presented in this study provides a comprehensive tool for both key performance indicators; remaining well potential and well risk, that are usually required to short-list wells for workovers. The standardized audit process was demonstrated in a case study where a large number of shut-in wells from multiple mature oil fields were ranked. In this study, the 7 highest ranked wells were recognized as production enhancement candidates and conversely, a number of wells with the lowest ranking were identified for well abandonment. Through this standardized workflow, the well risk assessment was performed efficiently with tools that enable a consistent result across different fields. It helped to accelerate the reservoir management decision-making process in identifying wells with the most impact to increase the success probability during inactive well revival and workover. The workflow and the tool presented in this paper has the potential to be used as analytic tool or template and can be used as a live document that may be adopted to reduce the workload and improve shut-in well management.

A recent study addressed the modelling challenges of Alpha* gas condensate field. Alpha gas condensate field has a gas in-place of about 1 TCF, and both condensate and black oil production in addition. The field has been producing from two reservoirs S-I and D-I, for the past 26 years. Alpha field is sub-divided into two segments called the Central Area and the Northern Area which are separated by a fault as shown in Figure 2. * Not its real name.

The subject Gas Field is located in the Sulaiman Fold Belt (SFB) in Pakistan. A realistic 3D static model was constructed for the challenging multiple reservoirs in the Field which included both clastics and carbonates. Four main reservoir horizons were modeled. The steps involved in the Reservoir engineering analyses were: analyze PVT, well test, Static Pressure Data, and Core. The static pressure analysis helped define hydraulic compartmentalization in the field. WHFP measurements were not available in the desired accuracy and density. A surface network model was used with plant inlet pressure as the primary constraint in order to obtain the required information. Satellite based elevation information was used to establish an accurate model with respect to pressure drop due to liquid hold up in pipelines. The History Match in the field was performed on a Zone by Zone basis. In the absence of a 3D seismic cube, many of the faults in the field could not be interpreted, yet their presence was predicted by a closely matching Sand Box Model. This was an important clue which led to a useful approach regarding the location of simulation faults distributed in the entire field. An innovative approach was used in order to calibrate the size of sand lenses in one of the zones. The final step was the forecasting and development of Optimal Scenario using Economic analysis. Many scenarios were tested, and the optimal scenario was identified. Maximum use was made of existing wellbores through re-completion, and new drilling was minimized. Furthermore, the impact of increasing the currently low Gas Price was tested. It was concluded that doubling of the gas price of the field would increase the NPV 3 times delay abandonment by 6 years.

Wireline formation testers are now in their third generation of development. These tools are used to measure formation pressure andpermeability, and to take fluid samples from the reservoir. Technological developments over the years have resulted in a modular tool that can obtain a clean formation fluid sample with minimal contamination. Sampling time varies from a few minutes to many hours depending upon different parameters i.e. depth of invasion, flow rate, formation permeability, anisotropy, porosity and the viscosity of the involved fluids including mud filtrate and formation fluids. Total pumpout time required to obtain a clean sample is always of interest to both the operator and service company owing to economics, well stability and other factors. An approach is required that is flexible and that requires few parameters to estimate the pumpout time and the time for first formation fluid slug. In this study a new polynomial model is developed to better estimate the time to first slug. The new model was tested for different pumpouts from different wells and history matching was performed to test the accuracy of the model. A number of pumpouts were considered and all of those showed close matches. Software was developed to quickly calculate the total pumpout time at real time. Also in this study the previous model was tested and with the limited available data the new model showed much improved results over the previous model.

As an increasing percentage of the world’s production comes from mature fields, there is a growing need for production enhancement techniques that are both rapid and easy to use for the practicing production engineers. For mature waterfloods, the ln(WOR) versus Np plot enables rapid well screening on the basis of incremental recovery factor, where WOR is the producing Water Oil Ratio and Np is the cumulative oil production. Published in-depth information on application of this tool is sparse. Yet, this is often the only tool available to the production engineer for evaluating development options, where a history-matched simulation model has not been maintained. In this paper, the theoretical basis for the use of the ln(WOR) versus Np is reviewed and studied, and is used to arrive at practical guidelines for interpreting production data. Its applicability as a forecasting tool to single-layered and multilayered clastic, waterflooded reservoirs of varying heterogeneity is demonstrated. Numerical simulation models then predict the behaviour of this plot for a wide range of heterogeneities. Production data is then analysed to show the applications of the theory for multilayered reservoirs. The ln(WOR) versus Np plots are analysed, and the impact of various factors is observed. The authors also demonstrate that, where applicable, this plot is the preferred decline curve for the following reasons: –Ln(WOR) versus Np does not require any pressure data; only surface well test production history is required.–It can be assumed that the ln(WOR) versus Np function is an approximate function of the reservoir only, and is decoupled from the outflow and facility constraints. This is especially useful when comparing artificial lift and drawdown strategies.–It is a decline curve model that provides a forecast of water cut, which is indispensable on waterflood projects.

In many oil wells, production is commingled from several layers. In such environments, understanding the properties of individual layers is essential to reservoir surveillance and production optimization. The inflow properties that typically require measuring are productivity index (PI), water cut, and static reservoir pressure. These measurements have traditionally been taken with wireline-conveyed production logging tools (PLT); however, in many wells and operating environments, completion and logistic considerations make running these tools difficult or even impossible. In those instances, an alternative is required. This paper presents a new procedure based on multirate testing in combination with distributed temperature sensors (DTS), an electric submersible pump (ESP) fitted with a gauge in the commingled fluid stream, and conventional surface testing. The additional test rates provide sufficient equations to resolve all the unknowns, whereas the DTS provides essential information such as which layers are producing and which are taking fluid, as well as a mass flowrate tool for measuring the flow rate of each layer. The procedure requires varying well flow rates over a range sufficient to ensure that all layers are producing, which in many cases requires an ESP to provide sufficient drawdown to overcome crossflow as well as a variable-speed drive to establish the test rates. The theoretical basis for the protocol is described, and an example is detailed to demonstrate the validity and robustness of the method for determining inflow properties. Finally, theoretical and practical guidelines are provided to demonstrate how the test procedure is affected by fiber-optic resolution, fluid properties, and the geothermal gradient. For wells equipped with forms of artificial lift such as ESPs, beam pumps, and progressive cavity pumps (PCPs), running PLTs is often not possible because of the completion obstruction. In such cases, this new DTS-enabled procedure has the potential of becoming the PLT substitute of the future.

A Paleocene dolomite in northeastern Libya was modeled using three porosity types: matrix porosity (intercrystalline plus the separate vugs), horizontal-to-subhorizontal solution-enlarged vuggy porosity generated by dissolution and named "touching vugs," and fracture porosity. The touching vugs, which acted like fractures in their dynamic behavior, are modeled as a very permeable discrete fracture network (DFN) in PETREL* seismic-to-simulation software. Their presence is known primarily due to pressure buildup analysis, and it is expected that they would be interconnected over hundreds of meters. The primary challenge in dual-media modeling is being able to characterize and predict the dynamic behavior of the complex matrix + fracture + touching vug system. There are three wells in this area of northeastern Libya with pressure buildups that have an unusually distinct and pronounced dual-porosity signature. Each well has been matched by adjusting the five primary parameters: matrix and fracture porosity and permeability, and the sigma shape factor. Aquifer strength also had to be adjusted. There are some aspects of the dynamic behavior of this reservoir that are of particular interest: The highly fractured low-porosity parts of the reservoir are the least productive, and the least fractured high-porosity parts with touching vugs are the most productive.The well test shows pronounced dual-porosity behavior and indicates a high level of contrast between the matrix and secondary porosity systems, both in terms of permeability and porosity.There is a strong aquifer and in reservoirs with moderate fracture permeability, we would expect to see the fractures provide a pathway for rapid water breakthrough. Owing to the very high permeability associated with the fracture system, this does not happen as expected; i.e., the reservoir acts to some extent like a tank with a level oil/water contact (OWC). There is not much coning or advancing of water in the secondary porosity system. This paper presents the dynamic features of the reservoir and demonstrates how the simulation model was calibrated using all available information, in particular, the pressure buildups.

A study was carried out to forecast the productivity of a hydraulically fractured well in a retrograde gas-condensate sandstone reservoir using a numerical model. The fracture was explicitly modeled as a set of high-conductivity cells. At the gas velocities normally encountered in hydraulic fracture proppant packs, non-Darcy pressure drops dominate, and the apparent proppant permeability is one or two orders of magnitude lower than the Darcy permeability measured at single phase low-rate conditions. This is particularly true if a liquid phase is also flowing. The apparent permeability of the proppant is a function of: Gas velocity (hence: rate and flowing pressure)Ratio of free liquid rate to gas rateStress on the proppantType of proppant Thus, apparent proppant permeability will vary with distance from the wellbore, increasing towards the tip of the fracture where liquid ratio and velocity are lower. This variation of permeability was explicitly modeled in the proppant pack by dividing it into segments and calculating the permeability in each segment. As a result of this modeling, the impact of increased fracture length on productivity was found to be more significant than in simpler modeling where one permeability value is used for the entire proppant pack. The variation of apparent proppant permeability along the length of the fracture and its impact on well productivity are discussed in this paper. A comparison of predicted well productivity is also made with the use of a constant permeability value for the proppant in numerical and analytic simulators. We will show that using a constant proppant permeability value results in an estimate of optimal fracture length that is too short.

An innovation in the methodology of conducting drillstem tests (DSTs) in tight gas reservoirs is presented, along with a simplification in the interpretation of the data obtained. DSTs in tight gas reservoirs are a problem because the flow rates are often too low to be measured by conventional equipment. In these cases a normal flowing and buildup test should be followed by a closed chamber test to produce usable estimates of flow rates at various times during the preceding normal flowing and buildup test. This estimated flow rate can then be used to interpret the buildup after the flow testing, which is produced by shutting the downhole valve. In the interpretation of DST data from a tight gas reservoir, factors such as the following have to be considered: 1) large variation of gas properties resulting from the large pressure range involved1,2; 2) flow rate duration that can be many times shorter than the buildup period3,4,5,6; 3) varying flow rate during the flowing part of the test; and 4) impact of boundaries and heterogeneities. We show that a simple interpretation approach with constant flow rates and pseudo-pressure yields results that are within the intrinsic accuracy limits expected from such a test. The benefits to the field interpreter of using the methods presented are 1) operational flexibility: if the well flows strongly enough the rate may be measured at surface; if it does not, a closed chamber test can be added; 2) the benefit of the deeper radius of investigation of a test flowing at surface is retained; 3) field interpretation is simpler whether surface measurement is possible or not.