Inflow Performance Relationship Curves Research Articles

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.

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.

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.

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.

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.

Establishment of the productivity prediction method of Class III gas hydrate developed by depressurization and horizontal well based on production performance and inflow relationship

Productivity prediction is one of the important issues for the economic and effective development of gas hydrate deposit. Therefore, this paper proposes a method to establish productivity prediction for the Class III gas hydrate developed by depressurization and horizontal wells. The method are divided into four steps, including numerical simulation, production performance analysis, revision of formulas and quantitative calculation of key factors. The prediction method is based on inflow performance relationship (IPR) of gas hydrate. Considering the shape of IPR curves, Fetkovich’s formula and Vogel’s formula are selected as the basic formulas respectively for the increasing part and decreasing part of gas hydrate production. To revise Fetkovich’s formula, the deposit pressure is replaced by comprehensive deposit pressure, which is determined by energy coefficient B0. Through the analysis and evaluation of influencing factors, B0 is described by a equation related to gas hydrate saturation. To revise the Vogel’s formula, the lowest production pressure is set as the four phase point pressure, leading to the change of production pressure difference and maximum gas production rate. The key coefficient C is calculated by a equation related to gas hydrate saturation and well spacing. Compared with simulation results, the results of proposed formulas show good accuracy in the prediction of production rate of gas hydrate. The results of test point predicted by revised Fetkovich’s formula almost coincide with simulation results. The average error between results of revised Vogel’s formula and simulation results is 4.24%. So the proposed method can be applied to predict the productivity of gas hydrate for its good accuracy, fast speed and simple calculation.

Predicting Stabilized Oil Well Inflow Performance Relationship on Unconventional Reservoir

Unconventional reservoirs are described as any reservoir that requires special recovery operations asides the conventional operating practices. However, low permeability affects the time it requires to attain stability. Presently, most of deliverability test is only carried out in a maximum 24-hour time. Limited test time makes it almost impossible to attain the reservoir stabilization time while carrying out the deliverability test. Meanwhile, to construct Inflow Performance Relationship (IPR) curve, the properties from stabilized time are required. This study aims to discuss how to predict the IPR curve by determining the stabilized flow coefficient value (C) on unconventional reservoir. Furthermore, the stabilized C was used to determine the Inflow Performance Relationship (IPR) for low porosity and permeability reservoir model, also known as Tight Oil Reservoir. The stabilized time and deliverability exponent value need to be determined before the stabilized C value. The stabilized time also know as pseudo-steady state time was evaluated from John Lee and Chaudry equation with validation from the reservoir model. The method proposed by Hashem and Kazemi, which employed the use of transient data in determining the flow coefficient value was also used. In addition, deliverability exponent (n) was determined using an equation proposed by Johnston and Lee. Furthermore, the backpressure equation from Rawlins and Schellhardt was used to construct the IPR curve.

A Novel Mathematical Model Considering Real Gas PVT Behavior to Estimate Inflow Performance Relationship of Gas Well Production

Inflow performance relationship (IPR) is one of the most important methods for the analysis of the dynamic characteristics of gas reservoir production. The objective of this study was to develop a model to improve the accuracy of the IPR for evaluating and predicting the production of gas reservoirs. In this paper, a novel mathematical model, taking into account the real gas PVT behavior, is developed to accurately estimate the inflow performance relationship. By introducing a pseudo-pressure function and a real gas properties database, this model eliminates the error caused by the linearization method and improves the calculation accuracy. The results show that more than 90% of the energy in the flow field is consumed by inertial forces, which leads to significant high-velocity non-Darcy effects in the gas reservoir. The reservoir permeability, original reservoir pressure, stress sensitivity coefficient, and skin factor have a great impact on the inflow performance relationship of gas reservoir production. This model predicts gas IPR curves with excellent accuracy and high efficiency. The high-precision gas well inflow performance relationship lays a solid foundation for dynamic production analysis, rational proration, and intelligent development of the gas field.

Optimization of inflow performance relationship curves for an oil reservoir by genetic algorithm coupled with artificial neural-intelligence networks

In this paper, the effect of parameters on the IPR (Inflow Performance Relationship) curves of a well is analyzed using a multilayer perceptron artificial neural network. Genetic algorithms were used to train the network to adjust the weights and bias of the network so that the RMSE (Root Mean Squared Error) of the data assigned to the network test was minimized. The algorithm also optimized the network structure (including the number of hidden layers and the neurons of each layer). Based on Eclipse software, one of the oil reservoirs was first analyzed and then by changing the average reservoir pressures (assuming the oil well is predicted to reach such pressures above the average reservoir) and pressures. For this purpose, 48 experiments were conducted concerning the research variables implemented by each of them, providing inputs and outputs for network training and testing. Finally, 85% of the data were allocated to the training section and 15% to the software-generated software using the artificial neural network test section. The basis for deciding the error rate of the test data was considered. About 100% accuracy in the regression indicates that the neural network is reliable in other performances. The defined error is less than 2%, which indicated the efficiency of the genetic algorithm to predict IPR curves. This is rooted in applying genetic algorithms as a training function because it has increased the accuracy of data training. The magnitude of ANN (Artificial Neural Network) error for each scenario is also shown in the following curve. For example, the error of the sixth experiment is reported to be around 8%.

Determination of skin factor using two different methods: pressure transient analysis and production data analysis

Skin factor is an important parameter in petroleum production engineering. Skin factor is used to optimize production, petroleum production analyzing and forecast, and help determine the Inflow Performance Relationship curve. Skin factor are usually determined by Pressure Transient Analysis which certainly causes the temporary close of the production, hence it also leads to the financial loss because of non-productive time of the well. In order to avoid this unwanted situation, this paper presented another method to determine skin factor using production data analysis. A workflow to calculate the skin factor is proposed for two different methods. The first method is based on production data analysis and the second one is based of the Pressure Transient Analysis. A process to estimate the skin factor by the Pressure Transient Analysis method was proposed which consisted of 6 main steps: collection of input data, data pre-processing, running model, model matching, selection of model, and sensitivity analysis. Another workflow using production data analysis was also proposed in this research to estimate the skin factor as well. The workflow consisted of three main steps: preparation of input data, selection of suitable flow regimes, and sensitivity analysis. The paper also pointed out the uncertainties of these two methods and how to deal with them in order to have highly reliable results. These proposed workflows for the two methods were then applied for a real case study with actual data and results were compared to analyze the feasibility of the proposed workflow. The factors affecting the accuracy of skin factor estimation were discussed also based on the obtained results. This research showed that it was possible to estimate skin factor daily based on production data because the difference between results obtained by the two methods were small and acceptable.

Calculation Method for Inflow Performance Relationship in Sucker Rod Pump Wells Based on Real-Time Monitoring Dynamometer Card

Based on the informatization and intelligent construction of an oilfield, this paper proposes a new method for calculating inflow performance relationship in sucker rod pump wells, which solves the limitations of current IPR curve calculation method in practical application. By analyzing the forming principle of the dynamometer card, the plate of abnormal dynamometer card is created innovatively, and the recognition model of abnormal dynamometer card based on “feature recognition” is established to ensure the accuracy of the dynamometer card. By analyzing the curvature of each point on the curve of downhole pump dynamometer card, the opening and closing points of standing valve and traveling valve are determined, and the models for calculating fluid production and bottom hole flowing pressure are established to obtain the data of fluid production and bottom hole flowing pressure of sucker rod pump wells. Finally, a calculation model of inflow performance relationship fitted with the calculated fluid production and bottom hole flowing pressure data based on genetic algorithm is established to realize calculation of oil well inflow performance relationship curve. The field application and analysis results show that the inflow performance relationship curve calculated by the model in this paper fits well with the measured data points, indicating that the calculation model has high accuracy and can provide theoretical and technical support for the field. Moreover, the real-time acquisition of dynamometer cards can provide real-time data source for this method, improve the timeliness of oil well production analysis, and help to reduce the production management costs and improve the production efficiency and benefit.

Tight gas production model considering TPG as a function of pore pressure, permeability and water saturation

Threshold pressure gradient has great importance in efficient tight gas field development as well as for research and laboratory experiments. This experimental study is carried out to investigate the threshold pressure gradient in detail. Experiments are carried out with and without back pressure so that the effect of pore pressure on threshold pressure gradient may be observed. The trend of increasing or decreasing the threshold pressure gradient is totally opposite in the cases of considering and not considering the pore pressure. The results demonstrate that the pore pressure of tight gas reservoirs has great influence on threshold pressure gradient. The effects of other parameters like permeability and water saturation, in the presence of pore pressure, on threshold pressure gradient are also examined which show that the threshold pressure gradient increases with either a decrease in permeability or an increase in water saturation. Two new correlations of threshold pressure gradient on the basis of pore pressure and permeability, and pore pressure and water saturation, are also introduced. Based on these equations, new models for tight gas production are proposed. The gas slip correction factor is also considered during derivation of this proposed tight gas production models. Inflow performance relationship curves based on these proposed models show that production rates and absolute open flow potential are always be overestimated while ignoring the threshold pressure gradients.

Oil Well Productivity Computation Based on a Brain-Inspired Cognitive Architecture

This paper aims to mitigate the negative effect of production data errors on the curve of inflow performance relationship (IPR). To this end, the author proposed a brain-inspired productivity computation method for oil wells based on Shannhan’s brain-inspired cognitive architecture. The architecture consists of two interacting sensorimotor loops. In the proposed method, the IPR parameters were fitted in the inner loop, and the fitting results were considered in the productivity computing in the outer loop. Then, the proposed model was applied to compute the oil productivity of a real oil well, compared with other common methods, and verified through numerical simulation. The results show that the new method can predict well productivity more accurately than the contrast methods. Suffice it to say that this research puts forward a simple and reliable method for IPR curve drawing.

Experiment on gas-water two-phase seepage and inflow performance curves of gas wells in carbonate reservoirs: A case study of Longwangmiao Formation and Dengying Formation in Gaoshiti-Moxi block, Sichuan Basin, SW China

Gas-water relative permeability was tested in the full diameter cores of three types of reservoirs (matrix pore, fracture and solution pore) in Gaoshiti-Moxi block under high pressure and temperature to analyze features of their gas-water relative permeability curves and gas well inflow dynamics. The standard plates of gas-water two-phase relative permeability curves of these types reservoirs were formed after normalization of experimental data. Based on the seepage characteristics of fractured reservoirs, the calibration methods of gas-water two-phase relative permeability curves were proposed and the corresponding plates were corrected. The gas-water two-phase IPR (inflow performance relationship) curves in different type reservoirs were calculated using the standard plates and validated by the actual performances of gas wells respectively. The results show that: water saturations at gas-water relative permeability equal points of studied reservoirs are over 70%, indicating strong hydrophilic; the dissolved cave type has the biggest gas-water infiltration interval and efficiency of water displacement by gas, followed by the matrix pore type and then fractured type; and the fractured type has the highest the permeability recovery degree, followed by the dissolved cave type and then matrix pore type. The calibrated gas-water two-phase relative permeability curves of fractured carbonate reservoirs can better reflect the gas-water two-phase seepage law of actual gas reservoirs and the standard plates can be used in the engineering calculation of various gas reservoirs. The characteristics of calculated IPR curves are consistent with the performance of actual producing wells, and are adaptable to guide production proration and performance analysis of gas wells.

Correcting Inflow Performance Relationship Curves for Explicitly Coupling Reservoir Simulations and Production Systems Simulations

There are many ways to integrate reservoir and production system simulations to forecast production, in a single model (implicit) or in coupled models (explicit). Explicit coupling, a simple and flexible coupling method, has the advantage of using commonly available commercial software to integrate reservoir and production systems simulations. However, explicit coupling may produce large deviations as the inflow performance relationship (IPR) curve, which combines well pressure and production and injection rates, can only be evaluated or amended at the beginning of a time-step. As the IPR curve changes during a time-step, it may be necessary to correct unstable results for well pressure and rates. Using a previously proposed IPR correction method, numerical stability was improved, reducing deviations during advancing the time step. A formula was created to support the correction of IPR curve. The methodology was tested using cases with known responses for pressures and flow rates, for a predetermined production strategy from the benchmark case UNISIM-I-D. Deviations were reduced to near zero when compared with uncoupled and decoupled methodologies to integrate reservoir with production system simulations.

Optimation Pressure Loss to Oil Production System with Electrical Submersible Pump (ESP) at the Well A SW Field Bojonegoro, East Java

Study about oil and gas well A and SW fields have been conducted in Bojonegoro area, East Java Province. From the research, it is known that one of the constrain in oil and gas production process is a pressure drop, so that is necessary to set Electrical Submersible Pump (ESP) as an artificial lift pump at low pressure wells. It is needed to analyze the production well pressure as an effort to optimize the fluid production. It is in describe to relations between IPR (Inflow Performance Relationship ) curve with TPR (Tubing Performance Relationship), are getting down point cut TPR curve with IPR curve, fluid rate its optimal, so need tubing’s diameter variation and the number of stage pump ESP variation to can the most optimal fluid rate. Produced that to tubing variation are 2,441 ID is 876,729 bpd, 2,991 is 961,197 bpd, 3,476 id is 996, 26 Bpd, while on the number of stage pump esp variation The most high is stage 400 with fluid rate 961,197 by comparison stage 338 it has value fluid rate 921,165 bpd, stage 200 it has fluid rate 827,889 bpd, and stage 169 has fluid rate 774,646 bpd. Of some variation tubing and stage pumps that has the most influence to fluid rate optimalize is the change number of stage pump.

Study of production enhancement through wettability alteration in a super-giant gas-condensate reservoir

Near wellbore condensate blockage phenomena commonly reduce gas production significantly. One efficient method for overcoming such problem is wettability alteration. Such issues as wettability state, treatment radius and time to reach the maximum level of production need be optimized prior to field application. In this paper, impact of these parameters are studied on gas and condensate production enhancement through wettability alteration. To do this, behavior of a well located in supergiant offshore Iranian gas condensate field is simulated and analyzed using a compositional model, single well and radial grid. The real fluid and reservoir properties of the studied well are utilized to construct the model. Different wettability states were defined using various relative permeability curves at various distances from the wellbore along with different treatment times are tested to find the best condition. Results indicate that near-wellbore wettability alteration leads to lower critical condensate saturation which has a significant impact on improving production parameters and reservoir recovery factors. Also, the highest recovery factor is achieved at optimal conditions where wettability is altered from strong liquid-wet to intermediate-wet at the small radius around the production well in early times. Furthermore, the inflow performance relationship curve (IPR) moves upward considerably which represents the magnificent production improvement.

Evaluation of the productivity of geothermal wells by analyzing production measurements and the damage effect

In this work, an analysis of production data for determining the damage effect in geothermal wells is reported. Measurements of some Mexican geothermal wells have been analyzed for evaluating the decrease of their productivity under exploitation conditions. As an innovation of the methodology used in this work, the dimensionless well flow parameters (pressure and mass flow rate), and the inflow performance relationship curves of producing wells were determined by using more representative thermodynamic properties of the geothermal fluid (i.e., characterized as a ternary compound system: H2O–CO2–NaCl). Geothermal inflow type-curves were therefore used for determining the wellbore damage effect. Production measurements of the wells were compiled at different stages of their operative life cycle. From this study, it was found that the wellbore damage effect increases with the exploitation time. These results enable a drop in the fluid flow mechanisms of the wells to be identified. The quantitative knowledge of the wellbore damage effect helped us to define a technical criterion for the decision making of the most appropriate engineering operations to be applied (e.g., cleanings, repairs, stimulations, fracturing, etc.) either to recover or to improve the well productivity. Copyright © 2016 John Wiley & Sons, Ltd.