Well-test Analysis Research Articles

Application of dynamic material balance to evaluate oil wells in Buzurgan oil field

The Material Balance Equation is a crucial tool utilized in reservoir studies to evaluate fluids and rock properties at static pressures. The Flowing and Dynamic Material Balance methods offer a significant advantage by avoiding the requirement to shut down wells, as they use flowing pressure instead of static pressure under constant or variable flow rates. The concept of "Dynamic Material Balance" involves converting the bottom hole flowing pressure at any point at any given time to the average reservoir pressure at that point. This allows for the use of classical material balance calculations and the development of classical material balance plots. In this study, the Dynamic Material Balance and Agrawal Type Curve techniques were used to estimate average reservoir pressures, initial hydrocarbon in place, and ultimate oil recovery for a well in the Mishrif reservoir, the main reservoir in the Buzurgan oil field. Many wells in this field experience problems such as high-pressure decline or continuous water production, necessitating ongoing evaluation. While the Dynamic Material Balance method focuses on boundary-dominated flow data, the Agrawal-type curve technique analyzes data from both transient and boundary flow periods. Agarwal decline curves were constructed using relationships of pseudo pressure normalized production, material balance pseudo time, and dimensionless variables in well-test analysis. The results from both methods showed comparable results with an absolute percentage error of (0.738) %, (3.07) %, and 5.7% for oil-in-place, drainage area, and average reservoir pressure, respectively. This strong correlation between the Dynamic Material Balance and Type Curve results indicates their accuracy and reliability.

SIMPLIFIED COMPUTATIONAL TOOL FOR PREDICTING FORMATION DAMAGE IN OIL WELLS

The present study underscores the significance of regular well test analysis to ensure the accuracy and consistency of data pertaining to the permeability and skin of exploratory wells. This study advances the development of a novel computer model, ASPIRE, which predicts formation damage in oil wells by analysing well-test data. In this context, identifying blocked pore throats in the formation close to the wellbore by paraffinic deposits (scales) and its influence on permeability necessitates routine well-test analysis. The software employs a modified linear regression model developed in this study to perfectly fit the well-test data's infinitely acting linear flow (IARF) region to a straight line. The cases "CASE 1" and "CASE 2" were considered for constant rate transient drawdown well test analyses. The findings indicate that Case 1, with a high skin factor, requires remedial action, such as stimulation, to increase the formation's permeability close to the wellbore for enhanced productivity. In contrast, Case 2 has higher permeability and lower skin factor than Case 1, so stimulation is not required. In addition, R-squared analyses were conducted to validate the results obtained from the developed tool. The analyses reveal an R-square value of 1 for all cases, indicating a 100% accuracy. Therefore, the study concludes that the developed tool is instrumental in accurately predicting formation damage in oil wells.

Rapid well-test analysis based on Gaussian pressure-transients

Reservoir performance forecasting technology commonly involves flow testing and fluid sampling in appraisal wells. This study introduces a new Gaussian Pressure Transient (GPT) method for rapidly evaluating well-test data. The GPT method provides an alternative for the current rate transient analysis (RTA) methodology, which relies on specialized knowledge and involves subjective steps of tangent line-fitting based on flow regime assumptions. The newly proposed method was validated with field well-test data and is different from the traditional PTA method in that it directly fits Gaussian well performance curves to well-test data. The GPT method can be used (1) to determine the uncertain reservoir parameters, and (2) predict future well productivity under production conditions. Well-test data from an offshore condensate discovery with low well deliverability are analyzed. The test data encompass five individual tests, all revealing low gas and condensate flow rates based on GPT matches. The method involves estimations of the hydraulic diffusivity and can generate both short-term and long-term well-performance forecasts. A sensitivity analysis explores the impact of the various parameters on the recoverable resource volume, identifying which data acquisition would be needed to improve the production forecast's accuracy. Validation with field tests and commercial simulator outputs demonstrates the model's robustness in formation evaluation and predicting well performance. The study recommends hydraulic fracturing for future field development, and includes simulation results valuable for reservoir management and decision-making.

Comparative analysis of filtering methods for measurement data from complex well configurations

This article presents a comparative analysis of various filtering methods for synthetic measurements that simulate data from well test analysis (WTA). The main objective of this work is to identify the most effective filtering methods for noisy WTA data, with the aim of preserving useful information and facilitating the subsequent interpretation of the results. The initial dataset consisted of 200 synthetic pressure drawdown (PDD) and pressure buildup (PBU) curves with varying levels of artificially introduced noise. Both classical filtering methods (Kalman filter, Savitzky–Golay filter, one-dimensional Gaussian filtering) and numerical methods based on neural networks (autoencoders) and machine learning (support vector machines) were considered for data filtering. The comparative analysis demonstrated that the performance of different filtering methods depends on the type of curve (PDD or PBU) and the well characteristics. The best results in terms of signal-to-noise ratio (SNR) and root mean square error (RMSE) were achieved using modern autoencoder-based methods. The conclusion is that the choice of an optimal filtering method requires a detailed analysis of the specific problem and the characteristics of the input data. A combination of different filtering methods is proposed to improve the quality of processing and interpretation of WTA data for complex well designs. The obtained results have practical significance, as they can simplify the segmentation of PDD and PBU curves, which is necessary for the correct identification of various operating periods of the well during the investigation process.

Assessment of Fracture Density Distribution from Image Logs for Sensitivity Analysis in the Asmari Fractured Reservoir

Characterizing fracture properties in naturally fractured reservoirs poses a significant challenge. While welltesting remains valuable, it often fails to provide precise descriptions of these properties. Bridging this gap requires the integration of geological expertise to enhance fracture assessment. This study addresses the limitations of well-test analysis and explores the application of Conventional Image Logs in structural, fracture, and geomechanical analysis. However, effectively combining these applications with well-test analysis on a field scale reveals a substantial knowledge gap. A critical challenge in this context is the absence of a defined procedure for calculating the variable "σ," a crucial parameter for simulating fractured carbonate reservoirs using image log fracture density. Integrating geological knowledge is essential to reduce uncertainties associated with well-test analysis and provide more accurate characterizations of fracture properties. Image log data processing emerges as a valuable avenue for gaining insights into the static attributes of naturally fractured reservoirs. This study focuses on Characterizing fractures using data from ten image logs and Developing a more accurate simulation model through the interpretation of images, with a particular emphasis on OBM imaging. The main goals of this fracture study revolve around establishing correlations between fracture densities well by well within the simulation and enhancing the accuracy of the simulation model by incorporating fracture data from image logs. Borehole imaging tools such as FMI/FMS and OBMI-UBI play a pivotal role in identifying significant structural features, including faults, fractures, and bedding. Fine-tuning fracture parameters during the history matching process, while potentially time-consuming, significantly impacts other historical match parameters. Consequently, the reliability of reservoir simulation results, predictions, and recovery enhancement strategies hinges on the precision of fracture properties and their distribution within the model. Recent advances in interpretation techniques have expanded the horizons of image interpretation, enabling the creation of more accurate simulation models for fractured reservoirs using fracture data obtained from image logs. The overarching goal of this project is to comprehensively evaluate a fractured reservoir field by integrating data from ten individual wells.

Evaluation of aquifer parameters through integrated approach of geophysical investigations, pumping test analysis and Dar-Zarrouk parameters in the central part of Bari Doab, Punjab, Pakistan.

In the central part of Bari Doab in Punjab Province of Pakistan, the factors such as sporadic rainfall pattern, decrement of water in rivers, subsurface salinity and excessive mining of groundwater have badly affected the hydrogeology and recharge system of aquifer. The present research work is an endeavour to evaluate the characteristics and potential of aquifer for its future sustainable availability within the study area of central part of Bari Doab. The geophysical studies, pumping tests data, borehole logs and Dar-Zarrouk parameters were used integrally to evaluate the aquifer hydraulic and hydrologic parameters in the study area. VES technique of geophysical investigations using Schlumberger electrodes configuration was carried out at sparsely distributed 435 locations. Litho-logs and VES results altogether decipher that the subsurface alluvial succession is primarily composed of intermixed layers of sand, gravel, clay, silt and some kankar inclusions. The VES data allied with pumping test analysis of test wells in the study area were used to evaluate the aquifer hydraulic properties. Comparatively low values of discharge rate, hydraulic conductivity and transmissivity were evaluated in two wells whilst relatively higher values of these parameters were evaluated in rest of six wells. The results of hydrologic parameters also confirm the results of hydraulic parameters in the wells. Finally, the Dar-Zarrouk parameters were used for the estimation of hydraulic parameters for whole study area and the aquifer zones of relatively high and low potential were delineated.

Productivity Analysis and Evaluation of Fault-Fracture Zones Controlled by Complex Fracture Networks in Tight Reservoirs: A Case Study of Xujiahe Formation

The development of tight gas reservoirs presents a significant challenge for sustainable development, as it requires specialized techniques that can have adverse environmental and social impacts. To address these challenges, efficient development technologies, such as multistage hydraulic fracturing, have been adopted to enable access to previously inaccessible natural gas resources, increase energy efficiency and security, and minimizing environmental impacts. This paper proposes a novel evaluation method to analyze the post fracturing productivity controlled by complex fault fracture zones in tight reservoirs. In this article, a systematic method to evaluate stimulated reservoir volume (SRV) and fault-fracture zone complexity after stimulation was established, along with the analysis and prediction of productivity through coupled fall-off and well-test analyses. Focusing on the Xujiahe formation in the Tongnanba anticline of northeastern Sichuan Basin, a 3D geological model was developed to analyze planar heterogeneity. The fall-off analytical model, coupled with rock mechanical parameters and fracturing parameters such as injection rates, fracturing fluid viscosity, and the number of clusters within a single stage, was established to investigate the fracture geometric parameters and complexities of each stage. The trilinear flow model was used to solve the well-test analysis model of multi-stage fractured horizontal wells in tight sandstone gas reservoirs, and well-test curves of the heterogeneous tight sandstone gas fracture network model were obtained. The results show that hydraulic fractures connect the natural fractures in fault-fracture zones. An analysis of the relationship between the fracture geometric outcomes of each segment and the net pressure reveals that as the net pressure in the fracture increases, the area ratio of natural fractures to main fractures increases notably, whereas the half length of the main fracture exhibits a decreasing trend. The overall area of natural fractures following stimulation is 7.64 times greater than that of the main fractures and is mainly a result of the extensive development of natural fractures in the target interval. As the opening ratio of natural fractures increases, the length of the main fractures decreases accordingly. Therefore, increasing net pressure within fractures will significantly enhance the complexity of fracturing fractures in shale gas reservoirs. Furthermore, the initial production of Well X1–10, which is largely controlled by fault-fracture zones, and the cumulative gas production after one year, are estimated. The systematic evaluation method in this study proposed a new way to accurately measure fracturing in tight reservoirs, which is a critical and helpful component of sustainable development in the natural gas industry.

Petroleum source rock potential evaluation: a case study of block 11a, Pletmos sub-basin, offshore South Africa

Among the several existing geochemical methods in hydrocarbon exploration, the technique linking total organic carbon content (TOC) and Rock–Eval pyrolysis is most widely used, largely as a result of its capacity to rapidly provide vital information regarding the identification of source rocks and their defining characteristic, as well as thermal maturity levels and generative potentials. In this study, data from prospective source units within the southern depocenter of the Pletmos Sub-basin were analyzed using this geochemical method. Cutting samples from six wells in Block 11a were subjected to organic geochemical analysis to understand the occurring hydrocarbon scenario. Based on the results of the investigation, five notable source rock intervals of Kimmeridgian to Turonian ages were identified. The source rocks are shales with both indigenous and non-indigenous organic matter. Their TOC values show a fair to excellent petroleum generating potential, with the Aptian and Kimmeridgian intervals having the highest and lowest, respectively. The Hydrogen Index (HI), along with S2/S3 ratio values, typifies a predominance of mixed type II/III (oil/gas-prone) with some type III (gas-prone) and II (oil-prone) kerogens. The trends of the maturity parameters Tmax and Ro (vitrinite reflectance) indicate maturities ranging from immature to a late stage of maturity (dry gas window). Two observed breaks in the Ro profile reveal a possible link of maturity to high heat flow that is allied to sedimentation and tectonic uplift during the Late Cretaceous. Generally, based on TOC, S1, and HI, the petroleum potential trend increases with increasing depth, with a striking display of mixed hydrocarbon generating potential. Interpreted hydrocarbon typing is thus recommended to support the well-testing analysis.

Pressure transient analysis of a horizontal well intercepted by multiple hydraulic fractures in heterogeneous reservoir with multiple connected regions using boundary element method

The focus of this paper is to establish a new general model framework considering both hydraulic fractures with finite conductivity and heterogeneous characteristics of multiple connected regions by using boundary element method. With this framework, we can calculate the pressure performance of any heterogeneous reservoir. The innovation is that the complex fracture flow, boundary shape and heterogeneous characteristics can be flexibly considered in the model. Transient pressure of fractured horizontal wells in heterogeneous reservoir is obtained by using Stehfest numerical inversion method. Subsequently, this proposed regional heterogeneity model was validated by using numerical simulation methods. The results show that the proposed heterogeneous model can be divided into five flow segments, which are bilinear flow, linear flow, radial flow, first boundary dominated flow and second boundary dominated flow. However, the research results show that the presence or absence of some flow sections is closely related to the regional permeability ratio and the regional storage capacity ratio. As the two most important parameters of heterogeneous reservoir, the permeability ratio and regional storage capacity of heterogeneous reservoir will have a huge impact on the pressure response and pressure field. The sensitivity analysis shows that these two factors will lead to the deformation of the pressure field distribution and affect the flow characteristics, and cause some flow segments to fail to appear. The smaller the regional storage capacity ratio, the deeper the V-shape, and the more fluid supplied from the outer zone to the inner zone. This study also suggests that the fracture conductivity mainly affects the early flow characteristics, and the smaller the conductivity, the greater the pressure loss. In addition, irregular boundary will also cause important deformation of pressure field, and the area size will affect the late flow characteristics, and the smaller the area, the greater the pressure loss. The new semi-analytical solutions can form a series of typical curves and be applied to the well test analysis of multi-stage fracturing horizontal wells in heterogeneous and unconventional oil and gas reservoirs. The findings of this study can help for better understanding of the influence of reservoir heterogeneity on pressure response and find some applications in well testing for inverse problems in heterogeneous reservoirs.

Metaheuristic algorithm integrated neural networks for well-test analyses of petroleum reservoirs

In recent years, well-test research has witnessed several works to automate reservoir model identification and characterization using computer-assisted models. Since the reservoir model identification is a classification problem, while its characterization is a regression-based task, their simultaneous accomplishment is always challenging. This work combines genetic algorithm optimization and artificial neural networks to identify and characterize homogeneous reservoir systems from well-testing data automatically. A total of eight prediction models, including two classifiers and six regressors, have been trained. The simulated well-test pressure derivatives with varying noise percentages comprise the training samples. The feature selection and hyperparameter tuning have been performed carefully using the genetic algorithm to enhance the prediction accuracy. The models were validated using nine simulated and one real-field test case. The optimized classifier identifies all the reservoir models with a classification accuracy higher than 79%. In addition, the statistical analysis approves that the optimized regressors accurately perform the reservoir characterization with mean relative errors of lower than 4.5%. The minimized manual interference reduces human bias, and the models have significant noise tolerance for practical applications.

Well - test analysis for wells with gas rich CO2 in carbonate reservoir Song Hong Basin

The evaluations of properties of carbonate reservoirs containing gas with very high carbon dioxide (CO2) content often face many difficulties. In fact, there is a significal difference in interpretation results compared to conventional gas well testing due to: there is a gas to liquid phase transition; noise, abnormal increase or decrease in pressure and temperature during flow period, etc. These abnormal behaviors are all directly related to the specificity of CO2 properties with high compressible than that of natural gas, which can vary greatly density and can reach supercritical liquid state, transitioning solid to liquid or liqid to gaseous states even when pressure and temperature changes within a small range. During the testing of gas wells with high CO2 content, the phenomenon of pressure drop while pressure buid-up often occurs, leading to the analysis of reservoir parameters according to the conventional pressure build-up analysis method usually not feasible. The content of the article is aimed at researching and applying the method of interpreting well test data in the drawdown period while multi-rate flowing to more accurately estimate reservoir properties and mitigate risks in the design of the field development plan to achieve the economic efficiency.

Analytical Fractured Reservoir Characterization by using Geological and Petrophysical Logs

Due to structural complexities in some wells, higher than the expected thickness of the Asmari formation is found. Fracture intensity and deep-rooted fractures broadly increase the risk of unpredictable water production. The well-test analysis is not sufficient in describing fracture properties. Unfortunately, the core condition is poor in the fractured zones and cannot be used to provide reliable information. So, the objectives of this study are developing an accurate structural model for the Asmari reservoir, and fracture characterization in the borehole by interpreting image logs and comparing the log's image results with core data. Dip classification based on a geological log has the value of providing a direct demonstration of structural origin and detecting Asmari fault and fracture systems and their impact on production and answering structural issues. So, in this study, the borehole imaging tools were interpreted to find solutions for fracture systems and fracture attributes. Interpreting accurate structural dip determined the structural problem, thus bringing the precise location of the well within the Asmari reservoir. Fracture properties (open or closed), occurrence, orientation, spacing, and porosity were interpreted using an Image log. The high density of fractures seen on FMS image logs in the study well has been confirmed by inspection of the cores and the distinction between major and minor fracture types from the FMS image logs has been established following core review. As a result, this exercise has been confirmed to be very valuable, not only for indicating the value of the log data, but it has also emphasized some significant limitations of the core data. The amount of information extracted from the FMS image logs goes beyond that achieved from the core. This exercise has validated why image logs are the main source of fracture information in the oil fields of Iran.

Application of a constructive method in solving the composite reservoir model of dual-porosity media with fractal characteristics

In this paper, we apply a constructive method to solve the extended Bessel differential equations with boundary value problem(BVP). Considering wellbore storage and skin effects, a dual-porosity composite reservoir model with fractal characteristics and three typical exterior boundary conditions is established. After symbolic comparison, the reservoir model is identical to the BVP proposed above, and the solving of the reservoir model is naturally reduced to the solving of the BVP. Based on the Laplace transform and a constructive method, the Laplacian space solutions of fracture system pressure and wellbore pressure in the two zones are obtained. The type curves of wellbore pressure and the pressure derivative are plotted with the aid of the Stehfest numerical inversion technique, the flow regimes are identified, and the effects of fractal and reservoir parameters on the type curves are analyzed. Compared with the traditional method, the similar constructive method is more efficient and fast in solving complex reservoir models, which is of great value in designing and implementing well-test analysis algorithms for complex reservoirs.

Calibration of naturally fractured reservoir models using integrated well-test analysis – an illustration with field data from the Barents Sea

This paper successfully applied the geoengineering workflow for integrated well-test analysis to characterize fluid flow in a newly discovered fractured reservoir in the Barents Sea. A reservoir model containing fractures and matrix was built and calibrated using this workflow to match complex pressure transients measured in the field. We outline different geological scenarios that could potentially reproduce the pressure response observed in the field, highlighting the challenge of non-uniqueness when analysing well-test data. However, integrating other field data into the analysis allowed us to narrow the range of uncertainty, enabling the most plausible geological scenario to be taken forward for more detailed reservoir characterization and history matching. The results provide new insights into the reservoir geology and the key flow processes that generate the pressure response observed in the field. This paper demonstrates that the geoengineering workflow used here can be applied to better characterize naturally fractured reservoirs. We also provide reference solutions for interpreting well tests in fractured reservoirs where troughs in the pressure derivative are recognizable in the data.

A new-generation Embedded Discrete Fracture Model calibration workflow applied to the characterization of complex naturally fracture reservoir

Characterizing natural fractures has a decisive effect on production forecasts in fractured oil and gas reservoirs. Discrete Fracture Networks (DFN) constitutes the main modeling framework for fractured geosystems. However, myriads of uncertainties are enclosed prior modeling representative stochastic or deterministic DFN ensembles. This paper presents a novel methodology for DFN calibration and an efficacious field application, which incorporates Well-testing interpretation, Embedded Discrete Fracture Model (EDFM) framework, and numerical reservoir simulation. The proposed workflow starts with the DFN generation from seismic data, imaging logging data and core data. After multiple DFNs are modeled, well-test analysis is employed to calibrate the intrinsic properties of fractures at different locations. Then, these fracture networks are characterized dynamically by EDFM, which promotes capturing the optimal fracture model quickly screened. Finally, pressure and production history match are reached for the DFN realization that honors the optimal fracture model.

New Correlation of Oil Compressibility at Pressures Below Bubble Point For Iraqi Crude Oil

Oil compressibility represents a significant character in reservoir simulation, design of surface facilities and the analysis of well tests, specifically for systems below the bubble point pressure. Oil compressibility is not directly measured in the laboratory. It is usually gained indirectly from experimental data recorded in PVT reports. The relative volume from the flash test is used to calculate oil compressibility at pressures above the bubble point pressure. At pressures below the bubble point, the reservoir behavior is simulated by the differential liberation test. The solution gas-oil ratio and the oil formation volume factor from the differential liberation test are employed in the estimation of oil compressibility at pressures below the bubble point pressure This paper purposes new correlation for calculating isothermal oil compressibility coefficient at and below bubble point pressure. The formulation of oil compressibility correlation is very difficult as it depends on many variables. This property is a function of many variables such as bubble point pressure, reservoir pressure, reservoir temperature, solution gas-oil ratio, oil formation volume factor, stock-tank oil gravity, specific gravity of gas and gas formation volume factor. Standing’s (1), McCain et al. (2) and Al-Jarri's (3) correlations were submitted for testing their validity to evaluate their performance with Iraqi crude oils and to compare their results with the results of the new correlation. The achievement of the new correlations has been done using two hundreds and nine data points from twenty PVT tests that were collected from Southern Iraqi fields. The evaluation of the previous correlations has achieved with graphical and statistical methods. These checking methods show a poor agreement between the observed and the calculated values. The checking methods (graphical and statistical) explain that the new correlation that was achieved in this paper is suitable to calculate oil compressibility below bubble point pressure for Iraqi crude oils.

Determining Reservoir Model Based on Welltest Analysis for Production Forecasting

Welltest analysis is basically an analysis of fluid flow behavior in porous rocks, both in oil reservoirs and gas reservoirs that aim to obtain reservoir characteristics. Welltest analysis is not only limited to get reservoir characteristics and well productivity, but to determine the reservoir and boundary models that are close to the real situation. Until now, to determine the reservoir and boundary models are usually assisted by using a simulator, which is called modeling. However, to determine the reservoir and boundary models has its own challenges, because there are no specific methods or equations that can know for certain the model of a reservoir. Choosing the right type of model also requires some consideration, such as seismic data, geological data, log data, and information provided from other wells drilled into the same formation. From the determination of this model can be used as supporting information for a reservoir, which is then used to be a predictive model and renewal of its geological model, as well as allowing engineers to simulate production estimates. In this paper, we will present an analysis of determining the right reservoir model based on welltest analysis, which selected model is used to simulate production estimates. Case example is taken from an oil well named "HBR-05", which has been carried out a pressure build-up test on one productive layer that until now has not been produced or closed since the well testing was carried out. From the determination of the reservoir model based on welltest analysis, obtained heterogeneous anisotropic reservoir model and rectangular-no flow boundary model. The selected reservoir model is used to simulate the estimated production of the "HBR-05" well if it is produced from this layer. Production forecasting results for 48 months (4 years) the "HBR-05" well, the cumulative production is 107.8 Mbbl. In addition, the results of forecasting show that the reservoir pressure is already below the bubble point pressure in the 22nd month of forecasting.

Transient pressure behavior of horizontal well in gas reservoirs with arbitrary boundary

Transient pressure analysis is a crucial tool to forecast the production performance during the exploration and production process in gas reservoirs. Usually, a regular shaped outer boundary is assumed in previous studies for well-testing analysis, which is just a simplification of practical cases and cannot reflect the actual boundaries of reservoirs. In this paper, a mathematical model is established to analyze the transient pressure behaviors of a horizontal well in an arbitrarily shaped gas reservoir. Dimensionless treatment, Laplace transformation, and boundary element method are applied in solving the model, which is verified by comparing with the results from the source function method. Based on the Stehfest numerical inversion method, the models of single-porosity media and dual-porosity media are solved respectively. Then, the time-domain curves of pseudo pressure and its derivative are obtained, and the flow regimes are identified. Finally, the impacts of some critical parameters on pressure transient behaviors are analyzed, including storativity ratio, interporosity coefficient, well length, and well orientation. This paper presents an effective way to handle complex external boundary problems in gas reservoirs.

Surface Pressure Data for Well-Test Analysis at a Joint Venture Gas Project in Sichuan

Surface Pressure Data for Well-Test Analysis at a Joint Venture Gas Project in Sichuan

Investigation of pressure transient analysis methods for single-phase and CO2-rich geothermal reservoirs

Geothermal reservoirs can undergo a transition from single-phase to two-phase or vice versa in their natural setting and during production. Some of these reservoirs can also contain considerable amounts of non-condensable gases, mainly (>90%) CO2. Thus, multi-phase and multi-component effects often complicate the analysis of geothermal well tests as pressure transient analysis (PTA) methods are mainly developed for single-phase flow and slightly compressible fluids.This work aims to investigate the suitability of commonly used PTA methods under two-phase and multi-component conditions. A series of numerical models were developed for a geothermal reservoir containing a mixture of water and CO2 incorporating the production/injection record and the corresponding pressure response. The pressure response of the numerical models was analysed to estimate the reservoir properties, and explore the accuracy of the interpretations. The parameters used in analytical models were also subjected to sensitivity analysis to identify their effect on the characteristic appearance of the pressure derivative plot for realistic interpretations of the reservoir characteristics.This modelling study demonstrates that geothermal reservoirs containing CO2 should be evaluated with great caution as the assumptions that analytical models do not take into consideration may have critical importance when assessing the well test derived properties.