Inflow Performance Relationship Research Articles

Developing an inflow performance relationship for predicting hydrocarbon recovery from horizontal wells operating in partially naturally fractured reservoirs under solution-gas drive

Inflow performance relationships (IPR) have long been recognized as one of the most important diagnostic tools for predicting hydrocarbon production performance. Current IPR models associated with naturally fractured reservoirs (NFR) are only applicable to fully fractured NFR models. No previous research has investigated the IPR of partially naturally fractured reservoirs (PNFR). This work aims to develop an IPR model for horizontal wells producing from PNFRs under solution-gas drive (SGD). A 3D black oil simulator is utilized to generate the required IPR data. A total of 236 IPR plots and 26 future IPR plots are generated throughout six major cases varying in fracture intensity (FI), dimensionless well length (LD ), matrix permeability (km ), and fracture porosity (ϕf ). Percolation theory validated the existence of a critical FI threshold at which complex IPR behaviors manifest. Sensitivity analysis reveals that IPR shape becomes more complex as LD reduces. ϕf has negligible effects on IPR and future IPR behaviors. A logarithmic cycle proportionality governs the relationship between km and absolute open flow potential (qo,AOF ) in future IPR curves. A generalized IPR model applicable to horizontal wells producing from SGD PNFRs is developed through the non-linear regression of IPR candidates. The model is validated against field data and complex IPR behaviors.

Desain dan Analisa Electrical Submersible Pump Pada Lapangan P-N 62 Sebagai Upaya Peningkatan Produksi

The reservoir pressure in the P-N oil well is currently showing a significant decline. Some oil wells cannot flow naturally, so artificial lift is required to maintain Jabung oil production and deplete the remaining oil reserves. Analysis and evaluation of the use of artificial lift electrical submersible pump (ESP) in the P-N62 well using calculation and simulation to see the production performance of a well after adding artificial lift based on the results of the calculation it is determined that the ESP TD800 Series-400 with 117 stages with the ability to produce up to 990.96 BFPD and has an efficiency of 58.67% which will be used to increase the production rate at the P-N62 well. Keywords: artificial lift; electrical submersible pump (ESP); Inflow Performance Relationship; petroleum

Analysis of scale problem using acidizing stimulation in field Z Kalrez Petroleum (Seram) LTD.

The annual decrease in production at well Z occurs due to scale deposits that impede fluid flow. Scale is a production problem due to the mixing of two types of water with different properties so that the solubility limit of the compound in the formation water is exceeded. To overcome the scale, stimulation is carried out with an acidizing method using a type of acid (HCL 10%). Evaluation was conducted to determine the effect of acidizing stimulation on scale based on productivity index (PI), inflow performance relationship (IPR) curve and comparison of stimulation methods. Evaluation of test results after acidizing stimulation of well Z experienced an increase in production. Productivity Index increased from 4.748 bpd/psi to 9.036 bpd/psi. Based on the IPR curve before acidizing, the maximum flow rate (Q max) = 324.107 bpd, increased to Qmax = 769.021 bpd. Based on the Cost Benefit Analysis (CBA), the Acidizing Stimulation method (10% formic Acid) was chosen to overcome the scale problem because the B/C ratio >1 or 1.9 means that for every 1 US$ invested in the Acidizing Stimulation method (10% formic Acid), a savings ratio of 1.9 will be obtained. So it is very reasonable to decide that the Acidizing Stimulation method (10% formic Acid), is feasible and more useful and efficient.

Effect of Gas-Oil Ratio on Oil Production for a Niger Delta Well

This study delves into the intricate relationship between gas-oil ratio (GOR) and oil production rate in a vertical well within the framework of reservoir engineering. The investigation employs advanced reservoir modeling techniques, drawing insights from Prosper software simulations and well data analysis. A comprehensive methodology involving PVT data, inflow performance relationship data, and sensitivity analysis guides the exploration of GOR's impact on oil rate. The selected well configuration, a vertical well, serves as the experimental canvas for this study. Through meticulous analysis of reservoir and well data, an Inflow Performance Relationship (IPR) curve emerges. This curve is developed using the Darcy reservoir model available within the Prosper software, reflecting the intricate interplay between fluid dynamics, pressure gradients, and production behavior. Further expanding the analysis, the study explores the IPR-Vertical Lift Performance (VLP) curve, spotlighting the well's behavior at a top node pressure of 250 psig. Subsequently, the study dives into the realm of sensitivity analysis, seeking to unravel the nuanced connection between oil rate, GOR, and well head pressure. The captivating findings are encapsulated, a visual testament to the intricate dance of fluid dynamics. The results paint a vivid picture of the GOR's role in oil rate modulation. The correlation between GOR and oil rate is revealed to be a delicate balance, illustrated by a crescendo and diminuendo as GOR rises beyond the bubble point. Above the bubble point, the gas's continuous expansion within the solution propels oil production. The study's intricate examination of well head pressure offers further illumination. The result further exposes the inverse relationship between well head pressure and oil production rate, as heightened well head pressure curtails pressure drawdown and subsequently reduces the amount of oil lifted to the surface. The study concluded that Oil production rate increases with increase in gas-oil ratio up to a maximum above which oil production starts decreasing. The decrease in oil production starts when gas is released from the oil. An increase in well head pressure led to a decrease in oil production. This is attributed to a decrease in pressure drawdown between the bottom of the well and the well head.

Revised inflow performance relationship for productivity prediction from marine sandy hydrate reservoirs in Nankai Trough

Productivity prediction is crucial for the safe and efficient exploitation of marine methane hydrate. As a feasible method, inflow performance relationship (IPR) can characterize productivity results and provide a theoretical basis for optimization of depressurization schemes. In this study, we propose two modified IPR models based on field data from limited trial production and numerical fitting in the Nankai Trough. Prediction results are obtained by depressurization, together with IPR curves under different recovery ratios. According to the conventional formulas, the reservoir pressure of the deliverability equation is revised, considering the dual contributions of hydrate dissociation and pressure drop. The comparison results show that the modified Vogel formula and Fetkovich formula can suitably describe the IPR for the single vertical well and horizontal well, respectively. Sensitivity analyses of various reservoir physical parameters indicate that changes in porosity and hydrate saturation cause diverse values for the undetermined coefficient A, primarily due to the alterations in the key coefficient pr′ in the revised Vogel formula for the vertical well scenario. However, absolute permeability has only a slight influence on the shape of the IPR curve. In contrast, absolute permeability plays a crucial role in affecting the Fetkovich-modified IPR curves for horizontal wells. Productions under varying porosities exhibit a consistent linear trend on the Fetkovich-modified IPR curve because of the comparable impact of gas production rate and pressure square variance. Besides, changing hydrate saturation can also have some effect on the IPR. Our research provides a feasible productivity prediction methodology for the safe and efficient extraction of similar hydrate reservoirs.

Fast production and water-breakthrough analysis methods demonstrated using Volve Field data

When producing from conventional fields, the well rates are primarily constrained by the production-system in the early years of the field-life, while later in the field-life the production rates are primarily constrained by the reservoir deliverability. For the post-plateau production period, the reservoir deliverability will no longer potentially exceed the production-system well-rate constraints. Traditionally, analytical equations are used in a nodal analysis method that balances the pressure at the well inflow point from the reservoir (inflow performance relationship; IPR) with the pressure required for the vertical lift performance (VLP; or vertical flow performance; VFP) from the same point upward. A faster and simpler approach is proposed in the present study. Whereas, the classical IPR solutions are based on a constant well-rate solution of the diffusivity equation, use of a constant bottomhole pressure assumption can bypass the need for nodal analysis type pressure matching solutions to obtain the well rate. Instead, the well rate can be directly computed from the pressure decline in the reservoir and any production system capacity constraint can be imposed on the theoretical well rate due to the reservoir quality. The merits of the new approach are explained and illustrated by way of a detailed production analysis case study using open-access data from the Volve Field (Norwegian Continental Shelf). In addition, the case study of the Volve Field wells demonstrates a new water-breakthrough analysis method.

Nodal Analysis of Naturally Flowing Wells in Faihaa Oil Field, Yamama Formation

This study focuses on the Yamama Formation, a significant carbonate reservoir in southern Iraq that is one of the most important productive reservoirs in the region. The Formation is characterized by porous limestone interspersed with thin layers of argillaceous and tight limestone. The Yamama reservoir in the Faihaa oil field is divided mainly into four units; YA, YB, YC, and YD. YA and YB units are considered to be the most important oil-bearing subunits due to their good petrophysical properties. The main objective of the study is to determine the optimum production rates of four naturally flowing wells in the Faihaa oil field using the Inflow Performance Relationship and Vertical Lifting Performance curves. The study investigates four critical parameters; tubing size, water cut, reservoir pressure, and wellhead pressure, and their impact on well performance. The study finds that wellhead pressure is the primary determinant of well performance, and deviations from the original tubing size have adverse effects on well performance. An increase in water cut beyond the recommended threshold, coupled with a reduction in reservoir pressure, results in decreasing well performance. The study underscores the importance of careful monitoring and analysis of these parameters to sustain and enhance well performance in the Faihaa oil field, providing valuable insights for well operators and petroleum engineers. The study's findings can be used to optimize well performance and increase oil production rates, with significant implications for the petroleum industry.

Artificial Lift Timing and Selection Optimized With Reduced-Physics Models

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 213089, “Optimizing Artificial Lift Timing and Selection Using Reduced-Physics Models,” by Hardikkumar Zalavadia, SPE, Metin Gokdemir, and Utkarsh Sinha, SPE, Xecta Digital Labs, et al. The paper has not been peer reviewed. _ The complete paper presents an artificial lift timing and selection (ALTS) methodology based on a hybrid data-driven and physics-based work flow. The proposed method predicts future unconventional reservoir inflow performance relationship (IPR) consistently and allows for continuous evaluation of ALTS scenarios in unconventional reservoirs with multiple lift types and designs. Continuous use of this process has been shown to improve production, reduce deferred production, and extend the life of lift equipment. Introduction The intent of the work flow is to maximize the positive economic impact of a well. The authors write that, to their knowledge, incumbent methods do not include the effect of subsurface performance. In the proposed approach, feedback is injected to the reservoir and a closed-loop response is obtained implicitly because of the selection of artificial lift type and operational parameters of that type. The hybrid reservoir modeling methodology is based on identifying transient well performance (TWP). The method is based on a novel formulation that combines diffusive time of flight (DTOF), succession of pseudosteady-state material balance, and transient productivity-index (PI) concepts for estimating dynamic reservoir deliverability. (Equations associated with these processes are provided in the complete paper.) This is combined with well-deliverability estimation for different artificial lift methods and their operating parameters to perform continuous nodal analysis and forecast phase rates using novel PI-based forecasting techniques. TWP Analysis This work establishes a practical method to estimate transient-well PI for every well at field scale to understand unconventional well performance. This transient PI then can be used in a variety of applications, including well forecasting, artificial lift planning, production optimization, and field development planning. The complete paper is focused primarily on using the TWP work flow for optimizing ALTS in unconventional reservoirs that is practical in its application at a field scale. Fig. 1 depicts the suggested work flow, which combines reduced-physics and data-driven methodologies to describe well performance over a series of steps. For TWP calculations, material balance is used through a sequence of pseudosteady states on the drainage volume evolution of a closed system.

Identifying Average Reservoir Pressure in Multilayered Oil Wells Using Selective Inflow Performance (SIP) Method

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently. Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ rates to surface conditions. Different types of Inflow Performance Relationship (IPR) equations can be used for SIP interpretation, including the Straight-line method, Fetkovitch method, and Laminar Internal Turbulent (LIT) relations. Although the SIP method can be used for single-phase flow, the interpreter can restrict the IPR’s calculations to a particular phase. This research discusses the difficulties in estimating the average reservoir pressure in multilayered reservoir completed wells over their production life. The SIP technique has been applied to some producing wells in the south of Iraq, which are completed in multiple producing reservoirs previously tested with a formation tester to estimate reservoir pressure and other parameters. Two wells are taken in the south of Iraq region, Zubair Oil Field, one with cross flow between perforations and the other well with no cross flow. An average pressure is not calculated for layer A in Well-1, because there is no contribution rate. While the average pressure for Well-1, layer B is 3414.49 psia. Also, the average pressure for Well-2, layer H is not calculated because there is no rate contribution from this layer, and the maximum average pressure was calculated in layer G, which is about 2606.26 psia. It is also found that the presence of cross flow has no effect on SIP calculations.

Development of a simulator for Inflow Performance Relationship analysis

Development of a simulator for Inflow Performance Relationship analysis

The inflow performance relationship in fractured, vertical, and dewatered coalbed-methane wells

Although not greatly studied, the inflow performance relationship (IPR) in dewatered and vertical coalbed methane (CBM) wells is essential in the development of a CBM reservoir. The dynamics of the stress sensitivity effect (SSE) and the matrix shrinkage effect (MSE), as well as the hydraulic fracture propagation, have all been neglected, especially for the exterior region, which is larger than the drainage radius. A novel IPR model has now been built that integrates dynamic SSE–MSE and hydraulic fracture propagation into the skin factor, and is validated with real production data from the Qinshui Basin, China. The absolute open flow rate given the SSE–MSE is 60.5% larger than without SSE–MSE. If the positive effect of the SSE–MSE on the permeability in the exterior region is neglected, the absolute open flow rate is reduced by 21%. The MSE has a greater effect on the fracturing skin factor than the SSE and tends to lower the fracturing skin factor, benefitting the production of CBM. Moreover, in light of the SSE or MSE, the non-Darcy flow effect is weaker due to restraints on the velocity of flow or the permeability. Useful and essential theoretical guidance for real CBM production can thus be gleaned from this novel IPR model.

Modeling analysis of coalbed methane co-production interference: A case study in Eastern Yunnan Basin, China

The interlayer interference in coalbed methane (CBM) co-production wells restricts the effective development of CBM resources in multi-seam areas; however, the establishment of quantitative interference indicators still remains difficult to date resulting from the complex geological formation evolution and reservoir development techniques. In this paper, the reverse flow rate and the water production inhibition index of the coal seam were derived from the transient inflow performance relationship (IPR) curve to characterize the interlayer interference. The IPR curves of different reservoir and aquifer parameters were calculated on the modified reservoir model using a CBM well as a case in East Yunnan Basin. From the data processing for obtaining interlayer interference indicators, the pressure difference between coal reservoirs was found to be the most critical factor in generating reverse fluids, with a 15% difference and the interference amounting to 244.08 m3 d·KPa−1, followed by coal seam thickness and permeability (∼18.00–25.00 m3 d·KPa−1). Gas content, Langmuir pressure, and Langmuir volume contribute slightly to the interlayer interference. Second, any increase in thickness or permeability of the aquifer will significantly increase the water production rate of the coal seam due to water influx. Significantly, the reverse flow rate will be increased when the aquifer is located in a higher fluid pressure system. Instead, the reverse flow rate will be decreased in the case of a lower pressure system. Finally, continuous pressure drops lead to the coal seam and aquifer recharge capacity higher than the set drainage system, resulting in the coal seam water not being removed effectively. The coal seam's water production inhibition index shows a positive correlation with the thickness and permeability of the aquifer and a negative correlation with the drainage intensity. The results of this paper bridge the gap between the identification interference indicators and the possible combination of production layers, and it also provides new insights for enhancing CBM development in the East Yunnan Basin.

A Semi-Analytical Approach for Calculating Productivity Index in Vertical Flowing Well: High Gas-Oil Ratio Field Data as a Case Study

Abstract The concurrent transport of hydrocarbon, water, and most times solids ensues all through the production system concerned in transporting multiphase fluid from the producing reservoir zone to the wellbore and then to surface. The flow capacity of a well can be estimated through the inflow performance relationship (IPR) that essentially depends on productivity index (PI). Productivity index is a vital and indispensable oil and gas industry tool for forecasting the deliverability and helps in economic feasibility studies of the well. The lack of a correct model for bottom-hole flowing pressure calculation has always been a challenge and results in erroneous estimate of productivity index of a production well. Numerous models on bottom-hole flowing pressure in wells have been recounted in different literatures over the years. Many of the earlier works were based on steady-state flow assumption, likewise not all the constituent terms that practically influence flow behavior of fluid in pipe were considered in derivation of the past models. In the present work, an enhanced semi-analytical model for determining well bottom-hole flowing pressure is offered where all the constituent terms practically influence flow behavior of fluid in pipe and employed in building the new model for estimating productivity index in a vertical well. This article builds a semi-analytical model for predicting flowing pressure at every flow transition period evidencing the water hammer pressure fluctuations often experienced at the start-up operation. Subsequently, the time-dependent flowing pressure obtained from the newly derived model was used to estimate the productivity index using high gas-oil ratio surface data from Niger Delta field. The result of productivity index obtained at steady-state period shows that the average prediction percentage error of the current approach is reduced to 3.78% compared to previously derived steady-state-based model by Guo et al. (2007, “A Rigorous Composite-IPR Model for Multilateral Wells,” Society of Petroleum Engineers, SPE 100923, San Antonio, TX, p. 11), Guo (2001, “Use of Wellhead-Pressure Data to Establish Well-Inflow Performance Relationship,” SPE Eastern Regional Meeting, Canton, OH, Oct., SPE 72372, p. 7), and Adesina et al. (2018, “A Realistic Model for Estimating Productivity Index of Vertical Well Using Wellhead Data,” Society of Petroleum Engineers, SPE-193506-MS) that, respectively, report as 18.59%, 5.23%, and 3.96%. The factors that influence the magnitude of water hammer pressure fluctuation at the start-up period have been identified through the derivation. The semi-analytical model improves the prediction accuracy and aids the reliability of design to avoid incidence of pipe burst due to pressure peak and serves as a tool to analyze the well performance.

A new correlation for calculating wellhead oil flow rate using artificial neural network

A separator and multiphase flow meters are considered the most accurate tools used to measure the surface oil flow rates. However, these tools are expensive and time consuming. Thus, this study aims to develop a correlation for accurate and quick evaluation of well surface flow rates and consequently the well inflow performance relationship. In order to achieve the abovementioned aim, this study uses artificial neural network (ANN) for flow rates prediction particularly in artificial lifted wells especially in the absence of wellhead pressure data. The ANN model is developed and validated by utilizing 350 data points collected from numerous fields located in Nile Delta and Western Desert of Egypt with inputs include; wellhead temperature, gas liquid ratio, water cut, surface and bottomhole temperatures, water cut, surface production rates, tubing cross section area, and well depth. The results of this study show that, the collected data are distributed as follows; 60% for training, 30% for testing and 10% for the validation processes with R2 of 0.96 and mean square error (MSE) of 0.02. A comparison study is implemented between the new ANN correlation and other published correlations (Gilbert, Ros and Achong correlations) to show the robustness of the developed correlation. The results show that the developed correlation able to predict oil flow rates accurately with the lowest mean square error.

Productivity Prediction of Fractured-Vuggy Reservoirs under Time-Varied Flow Rates and Bottom Hole Flow Pressures

Fracture-vuggy oil reservoirs contain micrometer-sized dissolved secondary pores, fractures, and meter-sized karst caves. Generally, the researches on the flow mechanism of fractured-vuggy reservoirs are based on the assumption of karst cave-fracture-matrix triple medium that gives a partial differential equation which the pressure satisfies. This triple medium flow equation lays the basics for the well testing theory of fractured-vuggy reservoirs. However, the triple medium equation cannot reflect the actual existence of the karst cave volume in geology. Recently, we proposed a theory of fracture-cave seepage flow coupled with vug pressure wave which takes the vug size into consideration and thus can better describe the fracture-vuggy reservoirs. On the basis of this theory, this work combines the change of formation pressure with time, Duhamel’s theorem, and well testing theory to obtain the mathematical expression of time-varied bottom hole pressure and flow rate in Laplace space. Then, the dynamic inflow performance relationship (IPR) curve of fractured-vuggy reservoir is obtained by inverse Laplace transformations. This dynamic IPR curve can predict the productivity for fractured-vuggy reservoirs using parameters from well test interpretations of pressure recovery. The correctness of this productivity prediction method is verified by filed fractured-vuggy oil well. This productivity prediction method not only utilizes and expands the application of well test interpretation data but also shortens the test time and reduces test costs, which is important for oil development.

STAGES NUMBER SENSITIVITY IN ESP DESIGN ON DIRECTIONAL WELL "X" SALAWATI FIELD

An Onshore Well “X” of the JOB Pertamina-Petrochina field is a directional well. This particular well has ESP as the artificial lift to deliver the production fluid to the surface. Due to the “off downhole”, oil production had been suspended since 2012. However recently, the well will be activated and the pump will be modified into the new one. The purpose of this modification is to find the most suitable and effective pump with the optimum number of installed stages on the ESP. This ESP design is started by nodal system analysis which correlates Inflow Performance Relationship (IPR) to Intake Pump Pressure. The calculation using the Pudjo Soekarno equation results in a maximum flow rate in this well is 446,33 BPD. The flow rate is targeted at 65% of the maximum flow rate. Therefore, ESP series 319 NBV 250-500/60 Hz is chosen considering the operating range around 231-416 BPD which in this case is inside the range. The pump will be installed at 8500 ft depth. The number of stages based on calculation is 270 stages capable to lift 300 barrels of fluid per day. This flow rate approximately meets the targeted flow rate, furthermore, the pump will be at 47,9% of its Best Efficiency (BEP) during the operation. With this result, the pump is considered able to operate efficiently and durably.

A Physics-Based Proxy for Surface and Subsurface Coupled Simulation Models

Summary Full-physics subsurface simulation models coupled with the surface network can be computationally expensive. In this paper, we propose a physics-based subsurface model proxy that significantly reduces the run time of the coupled model to enable rapid decision-making for reservoir management. In the coupled model, the subsurface reservoir simulator generates well inflow performance relationship (IPR) curves that are used by the surface network model to determine well rates that satisfy surface constraints. In the proposed proxy model, the computationally intensive reservoir simulation is replaced with an IPR database constructed from a data pool of one or multiple simulation runs. The IPR database captures well performance that represents subsurface reservoir dynamics. The proxy model can then be used to predict the production performance of new scenarios—for example, new drilling sequence—by intelligently looking up the appropriate IPR curves for oil, gas, and water phases for each well and solving it with the surface network. All necessary operational events in the surface network and field management (FM) logic (such as facility constraints, well conditional shut-in, and group guide rate balancing) for the fully coupled model can be implemented and honored. In the proposed proxy model, the reservoir simulation component is eliminated for efficiency. The entirety of the surface network model is retained, which offers certain advantages. It is particularly suitable for investigating the impact of different surface operations, such as maintenance schedule and production routing changes, with the aim of minimizing production capacity offline because of maintenance. Replacing the computationally intensive subsurface simulation with the appropriate IPR significantly reduces the run time of the coupled model while preserving the essential physics of the reservoir. The accuracy depends on the difference between the scenarios that the proxy is trained on and the scenarios being evaluated. Initial testing with a complex reservoir with more than 300 wells showed the accuracy of the proxy model to be more than 95%. The computation speedup could be an order of magnitude, depending largely on the complexity of the surface network model. Prior work exists in the literature that uses decline curves to replicate the subsurface model performance. The use of the multiphase IPR database and the intelligent lookup mechanism in the proposed method allows it to be more accurate and flexible in handling complexities such as multiphase flow and interference in the surface network.

Research on the Inflow Performance of the Plunger Lift in the Shale Gas Horizontal Well

Shale gas wells in the Changning block of Weiyuan, Sichuan, China, experience water production problems throughout their life cycles. In actual field production, plunger lift is typically used to discharge liquid from a shale gas well. However, it is difficult to test the formation inflow performance relationship curve (IPR) of a plunger lift well. Hence, data on the formulation and optimization of plunger lift well systems are lacking. Based on actual measured data related to casing pressure changes at the wellhead and the gas-liquid distribution characteristics in a wellbore during the shut-in phase, this paper establishes a method for calculating the formation IPR curve of a shale gas plunger lift well by calculating changes in wellbore gas volume continuously. This method has a fast calculation speed. The gas-water interface distribution can be obtained in 3–5 iterations, and the inflow dynamic curve can be calculated in less than 5 seconds. This method tested the IPR curves of gas wells in the Changning block. The IPR curves of plunger lift wells showed concave characteristics contrary to the conventional upward convex curves. This is because the bottom hole flowing pressure changes caused variations in the water saturation of the near-wellbore zone. Consequently, the productivity equation of the plunger lift well is established by introducing the variation coefficient of water saturation expressed by bottom hole flow pressure. This equation fits with the measured IPR curve with an average R2 of approximately 0.9989.

An Unsteady-State Productivity Model and Main Influences on Low-Permeability Water-Bearing Gas Reservoirs at Ultrahigh Temperature/High Pressure.

Currently, there is insufficient knowledge on the development of China’s low-permeability gas reservoirs under ultrahigh-temperature and high-pressure conditions; furthermore, the actual development process is difficult and has high technical demands. For example, the Ledong block in the South China Sea is a typical gas reservoir characterized using ultrahigh temperature (190 °C), high pressure (90 MPa), high water production, and low permeability (less than 1 mD). However, it is difficult to determine the factors influencing its production capacity, and the application of the traditional production capacity model is problematic because of the production of water. Accordingly, this study, which is based on the seepage theory, considers the influence of water production on the productivity of a single well; this study establishes an evaluation method for a low-permeability water-bearing gas reservoir vertical well (i.e., a highly deviated well) to determine how an unsteady state affects productivity. This method comprehensively considers stress sensitivity, initial pressure gradient, gas–water permeability, formation thickness, absolute permeability, supply radius, discharge radius, and well deviation angles to clarify the main factors affecting the productivity of single wells. Statistical methods are used to calculate and analyze the key influential factors, and this study provides quantitative evaluation methods to understand the productivity (and its influencing factors) of both vertical and highly deviated wells and the law of productivity decline. The model calculates the unblocked flow rate for 18 years as 319 × 104 m3/d. Compared with the actual production unblocked flow rate of 332 × 104 m3/d, the average error is 3.9%, which is within the allowed engineering range. Research shows the following order of factor influence on productivity: produced water–gas volume ratio > permeability > stress sensitivity coefficient > reservoir thickness > start-up pressure gradient > well deviation angle > discharge radius. Water saturation is the main factor affecting the unsteady-state productivity of gas wells in low-permeability gas reservoirs. In this study, with a production time of 100 days, the water saturation increases from 45 to 85%, and the open flow of the gas well decreases significantly from 30.1 × 104 to 1.6 × 104 m3/d, which is a decrease of 94.7%. Moreover, a continuous increase in the stress sensitivity coefficient, start-up pressure gradient, and water saturation caused a leftward shift in the inflow performance relationship curves of the modeled gas wells, whereas their production decreased.

A new comprehensive dimensionless inflow performance relationship for gas wells

Prediction of gas well deliverability is important for reservoir management. Conventional flow after flow, isochronal or modified isochronal tests are common methods for calculation of well deliverability. Single-point test using Vogel-type dimensionless inflow performance relationships (IPR) was also proposed to overcome the need for multi-point tests. However, analysis of field data showed that existing dimensionless IPR correlations fail to accurately predict well deliverability for some reservoir conditions. In this study, a wide range of reservoir rock and fluid data was used to develop a comprehensive dimensionless IPR correlation for calculation of gas well deliverability from single-point test data. Multi-point well test data from 61 different gas wells of 15 fields were used to compare predicted absolute open flow (AOF) and calculated AOF from multi-point test data. The data used for validation of the proposed dimensionless IPR cover a wide range of actual AOFs (2.1–1411 MMSCF/D). Good agreement between predicted well deliverability from new dimensionless IPR and that from multi-point test was achieved. In addition, superiority of the new dimensionless IPR to previous correlations was confirmed for a wide range of reservoir conditions through error analysis. The average absolute error for new model is 11.6% (standard deviation of 8.5%) while for the other models are 85.9% (standard deviation of 148.1%) and 68.6% (standard deviation of 115.3%) for a wide range of field data.