Production Data Analysis Method Research Articles

Study of inter-well interference in shale gas reservoirs by a robust production data analysis method based on deconvolution

In order to overcome the defects that the analysis of multi-well typical curves of shale gas reservoirs is rarely applied to engineering, this study proposes a robust production data analysis method based on deconvolution, which is used for multi-well inter-well interference research. In this study, a multi-well conceptual trilinear seepage model for multi-stage fractured horizontal wells was established, and its Laplace solutions under two different outer boundary conditions were obtained. Then, an improved pressure deconvolution algorithm was used to normalize the scattered production data. Furthermore, the typical curve fitting was carried out using the production data and the seepage model solution. Finally, some reservoir parameters and fracturing parameters were interpreted, and the intensity of inter-well interference was compared. The effectiveness of the method was verified by analyzing the production dynamic data of six shale gas wells in Duvernay area. The results showed that the fitting effect of typical curves was greatly improved due to the mutual restriction between deconvolution calculation parameter debugging and seepage model parameter debugging. Besides, by using the morphological characteristics of the log-log typical curves and the time corresponding to the intersection point of the log-log typical curves of two models under different outer boundary conditions, the strength of the interference between wells on the same well platform was well judged. This work can provide a reference for the optimization of well spacing and hydraulic fracturing measures for shale gas wells.

A Robust Density-Based Approach to Production Data Analysis of Oil/Water Multiphase Flow System

Abstract This paper presents a novel approach to estimate reserves of oil and water reservoirs undergoing boundary-dominated flow conditions in a simplified yet accurate manner. The methodology incorporates rescaled density-based exponential models and is based on the coupling of two-phase oil and water material balances with multiphase well deliverability equations. Current multiphase production data analysis methods employed for reserve calculations, including density-based approach, are subjected to the determination of saturation–pressure relationship, multiphase pseudo-pressure, and pseudo-time, as well as the iterative nature of its own algorithm. The herein proposed approach circumvents the need for pseudo-variables calculations, thus precluding the determination of saturation–pressure relationship and removing the iterative nature often present in state-of-the-art approaches. The proposed model is validated by comparing its predictions to numerical models with both constant and variable bottomhole pressure constrains, and has been found to match closely. For all cases, relative errors are found to be less than 1%.

A novel production data analysis method for multi-fractured horizontal wells with infill well-caused fracture interference

Tightening the well spacing for unconventional tight reservoirs is an efficient technique to enhance oil and gas recoveries. Infill well-caused fracture connection between wells is widely reported in the field with small well spacing. This will make it difficult to make formation evaluation and fracture characterization between wells compared to single well cases. In this paper, a novel production data analysis (PDA) method is proposed for fracture characterization with the consideration of interwell fracture connections after the hydraulic fracturing of the infill. The PDA method is based on a semianalytical model, in which the small-scaled fractures are treated with the concept of stimulated reservoir volume (SRV). Thus, the fracture connections between wells are classified into three types, including SRV, fractures, and both SRV and fractures. The physical model is discretized into several linear flow regions, so the mathematical model can be solved semianalytically. An integrated workflow is proposed to analyze the production data for the wellpad, and three steps are mainly included in the workflow, including PDA for the parent well before infill, PDA for the parent well after infill, and PDA for the infill well. In each step, the production performance in the early linear and bilinear flow regimes are analyzed with approximate solutions in the square and fourth root-of-time plots. Because only the relationship between unknown model parameters can be obtained with the approximate solutions, history matching to the production data in log-log plots is further used to determine each unknown parameter. The PDA method is benchmarked with a synthetic case generated by the numerical simulator tNavigator and a field case from Southwestern China. The results show that both good matches and precise parameters can be obtained with the proposed PDA method. The connected fracture number will not be sensitive in PDA when the wells are connected with high-conductive dSRV. The innovation of this paper is that a practical method is provided for PDA analysis of well groups with fracture connection, and it will be a good technique for fracture characterization and well-interference analysis for tight formations.

Integrated reservoir evaluation and simulation study for gas injection: a field case study

The objective of this study was to better understand the target oil reservoir through ensemble Kalman filter-based production data analysis, and to optimize the enhanced oil recovery strategy of the reservoir. We first improved our understandings of the heterogeneous properties by combining single-well reservoir simulation model with Ensemble Kalman Filter (EnKF) method. The reservoir properties along with other available in-formation in the geological and simulation models such as production history and well logs were then integrated in one simulation model. We carried out parametric studies to investigate the influence of four production parameters. We also developed the optimized EOR strategy of the target field based on the ultimate oil recovery and economics. Compared with traditional production data analysis methods, the EnKF-assisted production data analysis model from this study proves to improve the reservoir characterization in an accurate and practical manner. The work improved the understandings of Smackover formation and similar analogous fields. The strategic evaluation of in the study, together with the EnKF-assisted PDA model can facilitate the readers in making informed decisions for successful EOR development of their mature fields.

PENGARUH GAYA KEPEMIMPINAN TERHADAP SEMANGAT KERJA KARYAWAN PADA KOPERASI PT. PELAYARAN TONASA LINES KABUPATEN PANGKEP

PT. Pelayaran Tonasa Lines in Pangkep Regency is a company engaged in commercial and industrial equipment which is required to compete with other companies in the same field. Therefore, it needs a leader who can encourage its employees. This research aims to determine the effect of autocratic leadership style, participatory leadership style, and delegation leadership style on employee morale at the Cooperative PT. Pelayaran Tonasa Lines in Pangkep Regency. It was expected to find an appropriate leadership style for the cooperative PT. Pelayaran Tonasa Lines in Pangkep Regency. The impacts of each company's operational activities will automatically affect the environment and the community around the company running its business. One of the operational activities in the company is the production data analysis method used is multiple regression analysis. The research object was all employees of the cooperative PT. Pelayaran Tonasa Lines in Pangkep Regency that consisted of 49 people. The results showed autocratic leadership style had a negative and insignificant effect on employee morale, while the participatory leadership style and the delegation leadership style had a positive and significant impact on employee morale at the cooperative PT. Pelayaran Tonasa Lines in Pangkep Regency. The company's leader must establish appropriate intense communication among all employees so that problems and organizational development can be overcome jointly.

An Analytical Method for Parameter Interpretation of Fracture Networks in Shale Gas Reservoirs considering Uneven Support of Fractures

In shale gas reservoirs, the production data analysis method is widely used to invert reservoir and fracture parameter, and productivity prediction. Compared with numerical models and semianalytical models, which have high computational cost, the analytical model is mostly used in the production data analysis method to characterize the complex fracture network formed after fracturing. However, most of the current calculation models ignore the uneven support of fractures, and most of them use a single supported fracture model to describe the flow characteristics, which magnifies the role of supported fracture to a certain extent. Therefore, in this study, firstly, the fractures are divided into supported fractures and unsupported fractures. According to the near-well supported fractures and far-well unsupported fractures, the SRV zone is divided into outer SRV and inner SRV. The four areas are characterized by different seepage models, and the analytical solutions of the models are obtained by Laplace transform and inverse transform. Secondly, the material balance pseudotime is introduced to process the production data under the conditions of variable production and variable pressure. The double logarithmic curves of normalized production rate, rate integration, the derivative of the integration, and material balance pseudotime are established, and the parameters are interpreted by fitting the theoretical curve to the measured data. Then, the accuracy of the method is verified by comparison the parameter interpretation results with well test results, and the influence of parameters such as the half-length and permeability of supported and unsupported fractures on gas production is analyzed. Finally, the proposed method is applied to four field cases in southwest China. This paper mainly establishes an analytical method for parameter interpretation after hydraulic fracturing based on the production data analysis method considering the uneven support of fractures, which is of great significance for understanding the mechanism of fracturing stimulation, optimization of fracturing parameters, and gas production forecast.

Production Data Analysis and Practical Applications in the Sulige Tight Gas Reservoir, Ordos Basin, China

Successful exploitation of tight sandstone gas is one of the important means to ensure the “increasing reserves and production” of the oil and gas initiative and also one of the important ways to ensure national energy security. To further improve the accuracy of historical matching of field data such as gas production and bottom-hole pressure during the production process of this type of gas reservoir, in this study, a new expression of wellbore pressure for the uniform flow of vertical fractured wells in Laplace space based on the point sink function model of vertical fractures in tight sandstone gas reservoirs is constructed. This innovation is based on a typical production data analysis plot of the Blasingame type that uses the numerical inversion decoupling mathematical equation. After analyzing the pressure and pressure derivative characteristics of each flow stage in the typical curves, a new technique of type-curve matching was proposed. In order to verify the correctness of the model and the application value of the field, based on the previous production data of Sulige Gas Field in China, a new set of production data diagnostic chart of tight sandstone gas reservoir was formed. A case analysis showed that the application of the production data analysis method and data diagnosis plot in the field accurately evaluated the development effect of the tight sandstone gas reservoirs, clarified the scale of effective sand bodies, and provided technical support for optimizing and improving the well pattern and realizing the efficient development of gas fields.

Automatic Trend Tracking Model for Coalbed Methane Production Forecast

Nowadays, huge quantities of coalbed methane (CMB) well production data have been saved in the fields’ database, which declares that the industry of CBM enters the age of Big Data. The traditional gas production data analysis methods, such as the decline curve and type curve, are not effective for complex production conditions. So, we proposed an automatic segmentation trend tracking Model for the CBM production forecast, which is based on the production data and is more robust for the complex production condition.

Analysis of early-time production data from multi-fractured shale gas wells by considering multiple transport mechanisms through nanopores

Analysis of early-time production and flowback data from multi-fractured shale gas wells is of critical importance in the characterization of hydraulic fractures (HF). However, the accurate estimation of HF properties in the current models is challenged by the complexity in multiple transport mechanisms and two-phase flow of shale gas reservoir. This study presents a new semi-analytical method to estimate HF attributes for shale gas wells exhibiting two-phase flow based on straight line analysis. The proposed method considers two-phase infinite acting linear flow (IALF) and boundary dominated flow (BDF) for both HF and matrix domains. In addition, matrix flow considers desorption, diffusion, slip flow, continuum flow, stress dependence rock, and adsorbed water film in the nanopores. A modified material balance equation is proposed to calculate average pressure in the fracture and distance of investigation (DOI) in the matrix by considering gas desorption and diffusion in the matrix domain. The accuracy of the proposed method is tested against numerical results obtained from commercial software (IMEX-CMG). The validation results confirm that the developed method can closely estimate initial fracture volume, permeability, and permeability modulus from early-time production data exhibiting two-phase IALF and BDF regimes. Furthermore, the results indicate that the consideration of desorption, diffusion, and slip flow plays an important role in the modeling of gas transport in shale matrix. The impact of these transport mechanisms on production modeling as well as characterization of HF properties becomes significant when the matrix experiences substantial pressure drops. For the purpose of field application, the proposed method is used to analyze flowback data from a multi-fractured horizontal well. The field results reveal that the calculated fracture properties are consistent between the proposed method and the long-term production data analysis method.

A New Production Data Analysis Method of Shale Gas: Based on Flowing Material Balance Theory and Considering the Complex Flow Mechanisms of Multiple Pressure Systems

Shale gas has become one of the most important unconventional energy sources in ultra-low permeability reservoirs which has unique reservoir properties and exists in the form of free and adsorptive state in the reservoir, forming many kinds of flow mechanism. In this paper, we provide a new method for production data analysis of shale gas well based on the flowing material balance theory. This method can accurately and effectively evaluate the productivity of shale gas wells and the dropdown of formation energy. This new model divides SRV into matrix pressure system and hydraulic fracturing pressure system. Only 5 fitting parameters are needed to complete the productivity evaluation of shale gas well, and the pressure data of matrix system and hydraulic fracturing systems can be calculated by this model. Compared with the Hz Multifrac model in RTA, our model achieves better and more stable evaluation results in the application of typical production wells in many large shale gas fields, such as Fuling, Changning, Eagle Ford and Barnet.

A new sorption-corrected deconvolution method for production data analysis in a shale gas reservoir containing adsorbed gas

When characterising a reservoir with the production data acquired from a shale gas well, the rate-normalised pressure (RNP) method is widely used due to its simplicity. However, for sharply varying production data, such as production and shut-in of a well, the RNP method yields erroneous reservoir characteristics. On the other hand, the deconvolution method can overcome these limitations, but it is only applicable for linear pressure-rate relationships. That is, it is not appropriate for production data acquired from a reservoir containing adsorbed gas. This production data shows nonlinear pressure-rate relationship due to the compressibility of desorbed gas, which strongly influenced by the pressure. In this study, in order to utilise the deconvolution method to analyse sharply varying production data containing adsorbed gas in a shale gas reservoir, we propose the linearised relationship of the sorption-corrected pseudopressure and production rate by using a variable substitution method such that it can be correctly implemented for deconvolution. From the results of sorption-corrected deconvolution method, we conduct pressure transient analysis for obtaining shale gas reservoir characteristics. [Received: August 18, 2016; Accepted: January 28, 2017]

A new sorption-corrected deconvolution method for production data analysis in a shale gas reservoir containing adsorbed gas

When characterising a reservoir with the production data acquired from a shale gas well, the rate-normalised pressure (RNP) method is widely used due to its simplicity. However, for sharply varying production data, such as production and shut-in of a well, the RNP method yields erroneous reservoir characteristics. On the other hand, the deconvolution method can overcome these limitations, but it is only applicable for linear pressure-rate relationships. That is, it is not appropriate for production data acquired from a reservoir containing adsorbed gas. This production data shows nonlinear pressure-rate relationship due to the compressibility of desorbed gas, which strongly influenced by the pressure. In this study, in order to utilise the deconvolution method to analyse sharply varying production data containing adsorbed gas in a shale gas reservoir, we propose the linearised relationship of the sorption-corrected pseudopressure and production rate by using a variable substitution method such that it can be correctly implemented for deconvolution. From the results of sorption-corrected deconvolution method, we conduct pressure transient analysis for obtaining shale gas reservoir characteristics. [Received: August 18, 2016; Accepted: January 28, 2017]

A new evaluation method for determining reservoir parameters for the development of edge-water-driven oil reservoirs

Edge-water support is associated with many oil reservoirs. To develop this kind of reservoir, it is helpful to evaluate reservoir parameters such as well initial gas-in-place and aquifer energy. The evaluation of reservoir and aquifer parameters is an important prerequisite in making oil development plan. This paper focused a reservoir parameter evaluation method for use when reservoirs are driven by an edge-aquifer. This paper also proposed no–aquifer influx period-type curves and early aquifer–influx period-type curves that can be matched by well production data to determine reservoir and aquifer parameters. This method considers transient aquifer–influx models; curves are based on the Blasingame advanced production data analysis method and the simple-composite reservoir model. The purpose of the theory is to quantitatively evaluate the well initial gas-in-place, aquifer energy, and other reservoir parameters. This method first divides well history production data into three influx periods: no-aquifer, early aquifer, and middle-late aquifer. The no–aquifer influx period-type curves are matched with the corresponding no–aquifer influx period data, then the dimensionless drainage radius and positioning of the field well production data relative to type curves can be obtained, and next well initial gas-in-place and other reservoir parameters can be calculated by the relevant equations. In the case of the dimensionless drainage radius, the early aquifer-influx period-type curves can be drawn, and the aquifer energy can be determined by matching the early aquifer-influx period data with the corresponding type curves. The method in this paper uses well production data to match. It does not need the reservoir pressure that is measured through well shutting-in and must be used in the empirical aquifer-influx model, which is convenient and more reasonable. The results of a conceptual numerical simulation model indicate that this method is reliable and can help to evaluate oil reservoirs and provide useful guidance in developing oil reservoirs with transient edge-aquifer drives.

A method for production data analysis considering significant discontinuities in unconventional reservoirs

A method for production data analysis considering significant discontinuities in unconventional reservoirs

A new method for production data analysis in shale gas reservoirs

For most shale gas wells, frequent shut-ins and nozzle size changing often occur, leading to significant discontinuities in production data. This study proposes a new production data analysis (PDA) method to address the abrupt change issue based on the virtual equivalent time. With the virtual equivalent time, the qualities of type curve matching and production data analysis can be improved when there are abrupt changes in production data. The mathematical model with a variable flow rate provides new definitions of normalized pseudopressure and pseudotime with consideration of the pressure dependent permeability for multi-fractured horizontal wells in shale gas reservoirs. Subsequently, the virtual equivalent time is calculated based on the average formation pressure to consider the abrupt changes of the production data, which also can reduce the time of superposition principle calculations. Duhamel's principle, Laplace transform and inversion, and Newman's method are employed to solve the PDA model, which is validated by analytical and numerical solutions. Then sensitivity analysis are performed on the dimensionless constrained axial modulus, which shows that the larger the dimensionless constrained axial modulus, the lower and later the curves. Finally, a field case study is carried out using the proposed method. The results show that by using the virtual equivalent time, the matching qualities are good, and the issue caused by abrupt changes is satisfactorily addressed. Therefore, it has great potential for estimating the formation parameters and predicting the well production performance more effectively and practically.

A mathematic model for characterizing the relationship between coal reservoir pressure and fluid saturation

At present, the research on the gas water two-phase flow during the development process of coalbed methane reservoirs (CMB) is still weak. Numerous production prediction models and transient production data analysis methods have been developed. However, part of these previous models assume the single water or gas phase within the coal seams, the other part overlook the gradient of fluid saturation and pressure and another part investigate the effect of fluid saturation distribution on productivity by utilizing the concept of average saturation, which is obtained through the derivation of material balance equation in CMB reservoirs. Notably, the average saturation cannot capture the feature of saturation distribution in the coal seams. Therefore, the existed models do not take into account the influence of fluid saturation distribution characteristics on gas well productivity, which result in relatively large error between the present productivity model and the actual CMB wells. In these regards, according to the gas and water two-phase seepage differential equation, considering the stress sensitivity, matrix shrinkage, gas adsorption/desorption effect, this research establishes a mathematical model characterizing the relationship between formation pressure and saturation. Combined with gas-water two-phase relative permeability curve, the model can be solved to obtain the saturation distribution on the basis of reservoir pressure distribution. Moreover, the reliability of the model is verified against commercial numerical simulation software with excellent agreements. The proposed model fills the gap of CMB development theory, and significantly contributes to the precise calculation of the gas-water two-phase pseudo pressure. In addition, it lays a theoretical foundation for accurate prediction of CMB productivity.

RFID-based production data analysis in an IoT-enabled smart job-shop

Under industry 4.0, internet of things (IoT), especially radio frequency identification (RFID) technology, has been widely applied in manufacturing environment. This technology can bring convenience to production control and production transparency. Meanwhile, it generates increasing production data that are sometimes discrete, uncorrelated, and hard-to-use. Thus, an efficient analysis method is needed to utilize the invaluable data. This work provides an RFID-based production data analysis method for production control in IoT-enabled smart job-shops. The physical configuration and operation logic of IoT-enabled smart job-shop production are firstly described. Based on that, an RFID-based production data model is built to formalize and correlate the heterogeneous production data. Then, an eventdriven RFID-based production data analysis method is proposed to construct the RFID events and judge the process command execution. Furthermore, a near big data approach is used to excavate hidden information and knowledge from the historical production data. A demonstrative case is studied to verify the feasibility of the proposed model and methods. It is expected that our work will provide a different insight into the RFID-based production data analysis.

A practical method for production data analysis from multistage fractured horizontal wells in shale gas reservoirs

Shale gas reservoirs are characterized by gas adsorption in matrix and complex fracture networks after hydraulic fracturing stimulation, and the properties of which cannot be measured through existing methods. Many linear flow models have been proposed to interpret these properties, however the nonlinearity of desorption and gas compressibility is often neglected when analyzing production data. Moreover, the production rate and bottom hole pressure (BHP) are usually variable, while the control mode in analytical models is either at constant production rate or BHP. Therefore, the nonlinearity should be considered when interpreting production data, and the problem of variable rate and BHP remains to be solved. In this paper, a comprehensive method for analysis of production data with variable rate for multistage fractured horizontal wells in shale gas reservoirs has been put forward, in which the nonlinearity of desorption and compressibility is considered. The classical tri-linear flow model is modified by incorporating desorption in the matrix. New type curves are developed incorporating normalized rate, integration of the rate and derivative of the integration against pseudo-time. To analyze production data with nonlinear desorption and compressibility, modified material balance equation and material balance time are applied to process production data. If the production data of a real shale reservoir is given, the half-length and the permeability of the hydraulic fractures, the permeability of the stimulated reservoir volume can be determined with this method. Finally, a field case is used to demonstrate this method for production data analysis.

A similarity method approach for early-transient multiphase flow analysis of liquid-rich unconventional gas reservoirs

Despite their increased role in the global energy supply, liquid-rich unconventional gas (LRG) resources present a number of technical challenges. Among them, traditional production data analysis methods fail to successfully estimate and forecast production behavior in these systems. This failure is directly related to the extensive early-transient infinite-acting behavior exhibited by these systems, and the added complexities involved with liquid dropout and ensuing multi-phase flow of gas and condensate. Traditional approaches are strongly biased toward single-phase and boundary-dominated analysis; and when multiphase flow is considered, required input data often include laboratory-estimated pressure-saturation data and/or producing gas-oil-ratio data. In the present work, a novel extension of the similarity variable transformation method is developed to forecast production behavior in these LRG systems. The methodology uses the black-oil fluid formulation and considers linear and radial flow regimes under constant bottom hole pressure (BHP) and constant gas flow rate well conditions. Using this method, the system of governing partial differential equations is reduced to a system of ordinary differential equations solved by well-known Runge–Kutta techniques without the need for linearization. It is demonstrated that reservoir pressure and saturation behavior can be forecast simultaneously, thereby eliminating the need for pressure-saturation relationship or producing gas-oil-ratio data as inputs to the model. In all cases explored, the similarity results compared well to numerically generated reservoir data for a variety of well BHP and gas flow rate specifications. Calculated well production metrics also successfully matched data sets, indicating that this approach can be straightforwardly extended to estimate production metrics of interest during early transient conditions, such as liquid and gas production rates or gas-oil-ratio. Results strongly suggest that the method developed here provides a rapid and robust alternative to numerical simulation for forecasting of LRG reservoir systems.

A simulation method for modified isochronal well testing to determine shale gas well productivity

A simulation method to determine shale gas well productivity is developed based on modified isochronal well testing. The method is reliable and accurate and reduces the well testing time. First, the physical properties and wellbore parameters of the reservoir are obtained using the production data analysis method or well testing method. Then the production sequence and time sequence are determined. The production sequence is estimated by the production data analysis method, which can calculate gas well production under different pressures. The testing time interval and duration are determined by using the time value of the inflection points on the curve of the productivity coefficient and the time sequence. A modified isochronal well testing simulation model is developed based on the dynamic change patterns of the reservoir and well tubing, the production sequence, and time sequence. Finally, the simulation model is solved by the conventional production well test regression method, and the well productivity and open flow potential are calculated. Using a shale gas well in the Changqing oilfield, China, as a case study, field test results and simulation result are analyzed and compared. The results confirm the reliability of the new method in a shale gas reservoir; the precision of the shale gas productivity evaluation improved and the cost and duration of the test were reduced. This method can be expanded to other unconventional tight gas reservoirs.