A Flowback-Guided Approach for Production Data Analysis in Tight Reservoirs

Flow behavior analysis of two-phase (gas/water) flowback and early-time production from hydraulically-fractured shale gas wells using a hybrid numerical/analytical model

Present trends towards using high frequency and big data such as SCADA allow the acquisition of large set of well data ranging over much longer periods of time than previously imaginable such as total production history. Such production and pressure data can contain information about the reservoir at a substantially larger radius of investigation than that accessible to unconventional derivative analysis, which is limited to the interpretation of single flow periods at constant rate. By contrast, deconvolution methods, do not suffer from this constraint as they are designed to perform well production and pressure data analysis at variable flow rate. In this work, we present a deconvolution method applied to multi-fractured horizontal shale gas wells. This work offers a new solution method to the long-standing deconvolution problem and makes deconvolution a viable tool for well-test and production and pressure data analysis. The following objective is proposed for this work: To apply this method to traditional variable-rate/pressure problems, such as long-term production data, high SCADA frequency pressure gauge data and well tests having multiple wells producing. This paper will show the deconvolution method based on the work of Von Schroeter et al and Michael Levitan et al. Deconvolution is a mathematical tool that extracts the drawdown type curve from the rate and pressure history. Essentially, the deconvolution process consists of the following steps: Generate a typecurve as an initial guess Superimpose this typecurve with historical rate data to calculate synthetic pressures Calculate the error between the calculated pressures and the measured pressures Generate a new typecurve and repeat the process until the error between calculated and measured pressures is minimized Deconvolution techniques provide an alternative to unconventional diagnostic analysis, and can show additional flow regime information that would not normally be seen within the specified time-frame of the buildup test. The deconvolved typecurve can then be analyzed for each multi-fractured shale gas horizontal well using unconventional diagnostic analysis techniques to determine various reservoir characteristics such as Stimulated Reservoir Volume (SRV) fracture half length, permeability, skin, reservoir size, effective wellbore length, effective stimulated stages, and more. We validate our work with examples using daily and minute data. Upon validation, we then demonstrate the deconvolution method using a variety of field cases, including traditional well tests, turnaround wellhead gauge data as well as production data of multi-fractured horizontal wells. Our work suggests that the deconvolution method has broad applicability in variable rate/pressure problems and can be implemented in typical well test and production data analysis applications. This study highlights not only the need of combining different frequency and quality controlled data but also pressure and rate type of data as well to get a full understanding of various reservoir characteristics within the SRV.

Many fractured horizontal wells are completed in tight oil/gas or shale gas reservoirs which have significant networks of interconnected secondary fractures (SF). However, the existing linear transient dual- and triple-porosity models do not properly account for SF. While the dual-porosity model assumes negligible SF, the linear sequential triple-porosity model assumes negligible fluid transfer between the rock matrix and hydraulic fractures. Hence, the application of these models for production data analysis of fractured horizontal wells could result in unreasonable reservoir/fracture parameter estimates and hydrocarbon forecast. For this reason, the quadrilinear flow model (QFM) was developed to account for matrix—hydraulic fracture communication. Although QFM properly accounts for the contribution of SF during reservoir depletion, reservoir parameter estimation from its type-curve matching procedure has a high degree of uncertainty. This paper proposes simplified QFM flow regime equations to reduce the uncertainty associated with reservoir parameter estimation. This study carefully analyzes the general QFM solution by observing the flow regions from dimensionless rate and pressure type-curves. This solution is simplified by eliminating dimensionless parameters with negligible contribution to fluid depletion within the duration of each flow region. The resulting simplified equations are analytically inverted from Laplace space to time space. The simplification process 1) yields flow-region analysis equations for the specialized rate-normalized pressure and pressure derivative plots and 2) explains the possible physics behind the flow-regions. The effect of secondary fracture networks on reservoir depletion can be investigated by applying QFM analysis equations on specialized rate-normalized pressure and pressure derivative production data plots. The choice of these plots is based on operational well constraints and observable flow regions. The analysis equations are applied to interpret production data of two multifractured horizontal wells completed in the Cardium and Bakken Formations. The results estimate effective half-length of hydraulic fractures, investigate the presence/absence of secondary fractures and propose a workflow for handling the uncertainty in reservoir parameter estimation when applying the specialized analysis equation plots.

The reservoir model-based forecast uncertainty reduction requires the integration of multiple sources of information. Among them, production data are of great value. For this reason, a methodology able to manage them within the history matching process to improve the model calibration process is highly recommended. The scope of the activity is then to set up a new workflow able to fully integrate Production Data Analysis (PDA) with an Ensemble History Matching (ENHM) workflow. PDA outcomes represent evidence highlighted by the whole production history based on the collection, analysis, and integration of all available geological and dynamic data, such as injector-producer connections. A set of alternative realizations ("ensemble") needs to be created representing all the relevant uncertainties. Ensemble Screening is necessary to eliminate the non-PDA compliant realizations; comparing streamlines generated on the ensemble with the PDA outcomes and eliminating the non-representative realizations. Ensemble diagnostic tools can help to discriminate the ensemble consistency with the basic reservoir facts coming from PDA and which parameters or assumptions in the ensemble creation need to be revised because of the non-compatibility from a statistical point of view (like conflicting or insufficient parameterizations). The ensemble will be matched through the ENHM iterative process. The proposed workflow uses then the Fluid Path Conceptual Model (FPCM) derived from PDA, as a key driver to localize the model updates performed by the iterative ensemble process. The proposed workflow allows obtaining a set of realizations representative of both the main geological and dynamical features of the field. This in turn will result in a higher predictive quality of the model-based forecasts. The performed tests allow us to conclude that PDA outcomes provide significant information regarding the fluid communications that can improve the ensemble reservoir parameterization reducing the reservoir uncertainties. Ensemble distance computation based on streamline attributes, like Time of Flight and streamline normalized fraction, can find similarities among realizations reflecting the connectivity patterns relevant to the PDA perspective. The evidence highlighted from PDA can be used as firm input in the ensemble realizations generation also impacting fundamental steps, such as the geological setup. Moreover, PDA can help to identify the main uncertainty parameters characterizing the field and suggests a reasonable range of variability to be considered within the ensemble approach. Multiple ensemble diagnostic tools were developed to check the ensemble quality against PDA outcomes using different streamline attributes as a distance. Diagnostic tools, moreover, allow to identify a reduced number of model realizations representative of the ensemble variability on which run the forecast. The advantages of the proposed workflow can balance the unavoidable additional time with respect to standard ensemble history matching for its practical realizations on field cases, especially with many data and high model complexity.

Flowback rate transient analysis (RTA) is a practical tool for characterizing hydraulic fracture (HF) properties. However, the accuracy of the interpreted results from flowback RTA is challenged by the complexity in two-phase flow in the hydraulic fracture and matrix system. Accordingly, we present a new semianalytical method to characterize HF attributes and dynamics using multi-phase flowback data for tight and ultratight (shale) oil wells. The proposed method includes a two-phase diagnostic plot, a fracture RTA approach for straight-line analysis, and a matrix model capable of characterizing water and oil flow. The RTA approach is based on fracture infinite acting linear flow (IALF) and boundary dominated flow (BDF) solutions, which treats HF as an open tank with a variable production rate at the well and the contribution of water and oil from matrix within the distance of investigation (DOI). The pressure-dependent fluid and geomechanical properties, such as permeability and porosity, are considered in the pseudotime defined in fracture and matrix to reduce the nonlinearity of the system. We tested the accuracy of the proposed method against numerical results obtained from commercial software and verified its applicability by analyzing the flowback and long-term production data from a field example in Eagle Ford shale. The validation results confirm that our method can closely calculate water and oil influx from matrix as well as the average pressure and saturation in the HF and matrix DOI. The accurate estimation of the initial fracture permeability and pore volume demonstrates the applicability of the proposed method in quantifying HF properties from two-phase flowback data exhibiting fracture IALF and BDF regimes. The analysis results show that the estimated initial fracture pore volume shows more accuracy than initial fracture permeability due to the different calculation sources in the straight-line analysis. In short, the proposed method is, to our best knowledge, the first RTA approach incorporating the two-phase water and oil influx from matrix into the inverse analysis of fracture properties and dynamics using straight-line analysis, instead of history matching

During hydraulic fracturing, there is a temperature difference between the injected water and formation rock for shale gas wells. The objective of this study is to investigate how this temperature difference changes with time, and how it affects multiphase-flow modeling during the shut-in and flowback periods. We conducted numerical simulations to investigate the behaviors of fracture temperature in shale gas wells. The results show a significant increase in fracture temperature during the shut-in and flowback periods. Sensitivity analysis suggests that this temperature increase is strongly related to the thermal conductivity of formation rock, matrix permeability, and initial reservoir temperature. Simulation scenarios were further compared to investigate the effect of temperature on flowback data analysis. Without considering the thermal effect, flowback data analysis may yield an earlier fracture cleanup and overestimated fracture volume. In addition, this study suggests that the thermal effect may also have implications for optimizing flowback operations.

Horizontal wells and hydraulic fracturing are the key technologies that allow commercial production from tight oil and gas reservoirs. However, rigorous analysis of production data from these reservoirs requires incorporation of the impacts of stress-dependent permeability and multi-phase flow. Changes in the stress state of the system during production may reduce the absolute permeability. Furthermore, gas phase formation and flow in presence of supersaturated oil phase affects fluid dynamics in tight oil reservoirs. This study provides a rigorous methodology for incorporation of the effects of non-static permeability and multi-phase flow in rate transient analysis (RTA) of tight oil and gas reservoirs producing at variable rate/flowing pressures during transient linear flow period. Analytical solutions for the approximate linearized form of the flow equation have been widely used as the basis for RTA tools for conventional reservoirs during transient flow period. However, they lead to considerable error when applied to tight oil and gas reservoirs. In particular, during the transient linear flow period, the slope of the square -root-of-time plot obtained from numerical solution differs from the slope calculated by analytical methods. Efforts have been made by some researchers to obtain a correction factor from the numerical solution of the flow equation to correct the slope of the square-root-of-time plot for single phase flow of gas during transient linear flow period. In this study, an iterative method is used for evaluation of the slope correction factor in the presence of multi-phase flow and non-static permeability for constant-pressure production during transient linear flow period. Further, the correction factor is used for analysis of production data from tight oil and gas reservoirs producing at variable rate/flowing pressures. The correction factor is used in the analysis of different sets of synthetic production data for tight oil and gas reservoirs. The results show that the correction factor can reduce/eliminate the considerable errors associated with the conventional analytical methods in initial permeability estimation. For multi-phase flow cases, the producing gas -oil ratio (GOR) is used to estimate the oil saturation-pressure relationship in the reservoir, which is required for calculation pseudo-pressure and the correction factor. The method developed in this study alleviates the need for using numerical simulation models to generate empirical correlations for the correction factor for the square -root-of-time plot. The easy-to-implement iterative procedure of this method only requires the pressure dependencies of the constituent elements of the hydraulic diffusivity. Therefore, this method is applicable for analysis of production profiles for variety of reservoirs with nonlinear flow equations.

The measurements available to estimate reservoir parameters are numerous, yet most wells are completed in various shales without traditional log measurements. Horizontal wells continue to be drilled, and while the number of stimulation stages pumped per lateral length continues to increase, many questions remain: Is there an increase in production commensurate to the added cost, or will it soon become unsustainable? Would better characterization of the effective surface area after hydraulic fracture stimulation help explain the reservoir potential? Analysis of production data from fractured shale gas wells is difficult. Operators try to estimate fracture and reservoir properties for a horizontal well with multiple hydraulic fractures by using pressure transient testing, even though in reality it could take 10,000 years for the actual reservoir pressure to be measured. Alternatively, others model the production of fractured shale gas reservoirs from a zone-altered permeability area, which may be quite limited in areal extent but is surrounded by a low-matrix-permeability reservoir to account for the well productivity. Ultimately a simplistic reservoir model for production forecasting uses whatever data is available and our basin experience. How do we validate these models? Traditionally we look at case studies to find an analogous situation to validate and identify the dominate production drivers. Existing approaches to model shales require years of production data, and even then they cannot uncouple reservoir properties from completion parameters to help optimize flow efficiency. When production is measured on a stage-by-stage basis, and laboratory and log analysis data are presented for reservoir and fluid characterization, solving for the created effective surface area should be straightforward. By better characterizing along the wellbore and by discriminating the contributions of RQ and CQ to the reservoir production, we will be able to better predict long-term well production and better understand the reservoir potential. This paper discusses the current status of production prediction for shale gas reservoirs and provides a vision of possibilities for better interpretation, i.e these production models must go hand-in-hand with hydraulic fracture models to determine the crucial parameters that drive production, thus fully optimize well and field production.

Rate normalized pressure (RNP) and derivative (RNP') method uses the log-log plot of RNP and RNP' versus material balance time (te) to interpret formation and hydraulic parameters like permeability and fracture half-length. It's a very useful methodology and sometimes the only way to conduct transient rate and pressure analysis for shale gas wells because pressure buildup is rarely recorded. However, the method may be not applicable because material balance time is not a monotonic increasing function of time especially when the one well has a short production history and has big vibration of production rate. A new method is proposed to solve the above problem for shale gas wells. In the new method, the average material balance time (cumulative production (Np) divided by average gas rate) is used to replace te. Therefore, the increasing monotonicity with production time is guaranteed. Curves of te vs. production time and average te vs. production time are contrasted. Different field cases with smooth decreasing gas rate and the cases with sharp change rates are used to check the applicability for the proposed new method. The plots of RNP & RNP' vs. average te, RNP & RNP' vs. te are drawn for different shale gas wells data for accuracy comparison. Results show that the new method has similar type-curve with the RNP & RNP' vs. te method and can be used to interpret the formation and hydraulic parameters by diagnosing typical flow regimes for shale gas wells. Compared with the RNP & RNP' vs. te method, the new method theoretically improved the accuracy production date analysis because the x axis is a monotonic increasing function of production time while not showing inflection points in RNP & RNP' vs. te plots. Field case with smooth decreasing gas rate shows that the new method and RNP & RNP' vs. te method can both get satisfactory log-log plot match and rate & pressure history match. Although the RNP & RNP' vs. average te may give smaller SRV volume, the interpretation results for both methods are comparable. The shale gas case with sharp vibrated gas rate shows that the new method can get both better log-log plot match and rate & pressure history match, in return, the interpretation results may be more confident. The RNP & RNP' vs. average te method may improve the production data analysis (PDA) accuracy when the shale gas wells have huge rate vibrations which may be caused by fluid flow-back, choke size change, temporary well shut-in and etc. However, more shale gas wells data should be used to test the method.

The major factor influencing the increase of natural gas use is the rise in its global demand. Due to the relentlessly increasing demand, there have been improvements in the techniques and technology used in recovering natural gas from shale gas reservoirs, including drilling a horizontal well and hydraulic fracturing. One of the significant challenges associated with gas shale production is that it is difficult to reliably predict ultimate recovery and estimate reserves, leading to great risk in exploitation of these resources. The purpose of this research is to evaluate the current decline curve analysis techniques and provide a more reliable method for production forecast and reserve estimate for hydraulically fractured horizontal wells producing from gas shale reservoirs.;When production data of low permeability reservoirs are analyzed using Arp's equation, the decline exponent b which is supposed to range between 0 and 1 is usually greater than 1. The actual decline exponent b value is not easy to come by in the transient period during the life of the well, however, having a decline exponent b value greater than 1 will overestimate the remaining reserves of the well.;In this study, first, decline characteristics for shale gas wells are presented by simulating long-term production performance for a variety of well-reservoir systems, including Dimensionless fracture conductivity change, different fracture stages and fracture half-length; then different current decline analysis methods were evaluated in estimating reserves and predicting future performances. These methods are Conventional Decline Curve Analysis, the Backward Method and the Ilk Method. The evaluation task was done through quantitative comparison of production forecast results from current decline analysis with true simulated recovery.;Finally, the Backward & Ilk method was proposed and evaluated. This research work indicates that the Backward & Ilk method can provide the most suitable and accurate results in estimating reserves and analyzing production data.

This research presents the selection of an appropriate decline curve analysis (DCA) methodology according to the transient production performance of a multi-fractured horizontal well in an unconventional gas field by using the cumulative production incline rate (IQp) The IQp introduced in this research is the change of cumulative production per unit time divided by the cumulative production. The IQp was confirmed for use as an indicator that could generalise and quantify a production decline through the analysis of well production data. The IQp values of eight and four DCA methods were applied to the production data generated by a reservoir simulation. The Duong method forecasted the production trends most accurately when the IQp exceeded 0.25%, while the YM-SEPD method was the most preferable for the rates below 0.05%. In addition, the analysis of production data for shale gas wells in Canada and the USA matched the simulation results, confirming that it would be reasonable to use the IQp in order to select a DCA method to forecast the production of unconventional gas wells. [Received: February 23, 2017; Revised: December 7, 2017; Accepted: December 9, 2017]

Recently, flowback data analysis enabled us to evaluate important fracture parameters including fracture conductivity and volume in unconventional reservoirs. To perform the analysis, diagnostic plots, straight-line techniques, and history-matching techniques have been used. Immediate water and gas production usually occurs on flowback in shale gas wells. In this paper, a novel workflow is developed for the analysis of water flowback data and early-time production of shale gas wells. This analysis then helps to define the movable water and the applicability of the soaking process on the shale gas well. Rate transient analysis (RTA) combined with decline curve analysis (DCA) was used to analyze different shale gas wells. Effective fracture volume and geometry were calculated from the RTA analysis. Estimated ultimate water recovery was calculated from DCA. The calculated water-in-place and the estimated ultimate water recover (EURw) will be compared against the injected fracturing fluid. Water RTA result show that in the case of shale wells with no movable formation water, gas kick off early, and boundary dominated flow (BDF) was observed. In addition, these wells performance improved with soaking process. On the other hand, if initial formation water saturation is higher than the connate water, water production will be from the frac fluid and formation water. As a result, gas kick off delays and transient flow regimes are expected. Soaking process can have a negative impact on the well performance if the movable water saturation is high. Honoring the flowback data can help to estimate the fracture geometry and to judge the quality of the shale formation quality and its validity for soaking process.

Tight reservoirs stimulated by multistage hydraulic fracturing are commonly described by a dual porosity model. This model consists of homogeneous matrix blocks separated by vertical hydraulic fractures. This paper hypothesizes that the production data of some fractured horizontal wells may also be described by a triple porosity model. The third medium can be either reactivated natural fractures or thin horizontal beds with a higher permeability. We test this hypothesis by extending the existing triple porosity models to develop an analytical procedure for determining the reservoir parameters. We derive the simplified equations for different regions of the rate-time plot including linear and bilinear flow regions. These equations can be used to calculate the effective fracture half-length, matrix permeability and length of micro-fractures. We use the proposed model to analyze the production data of two wells drilled in Barnett shale. The results show that a dual porosity model is more appropriate for describing Barnett shale data. Even if the micro-fractures are present they are not inter-connected and the length scale is much smaller than the hydraulic fracture spacing. The second part of this paper focuses on analyzing production data of tight oil reservoirs. We plot rate-normalized pressure (RNP) versus material balance time (MBT) of two wells drilled in Cardium and Bakken formations. We observe a half-slope followed by a unit-slope in both cases. This paper hypothesizes that the half slope reflects the linear transient flow regime, and the unit slope reflects the linear pseudosteady state (PSS) flow. We test this hypothesis by developing a new model for pseudo steady state flow when pressure interference occurs between two adjacent hydraulic fractures. We determine the reservoir properties by both PSS and transient analysis methods. For Cardium well, both methods give very close results. For Bakken well, both methods give relatively close results. We conclude that analyzing the late time production data of tight oil wells complement the linear transient analysis and can be used to calculate the stimulated reservoir volume, which can eventually help the industry to optimize the fracturing operation.

To continue effective development requiring alteration of waterflood system and reduction of risks associated with infill sidetrack drilling of UV1 formation of Varingskoe oil field in Western Siberia, which is characterized by high water cut and presence of confirmed technogenic fracturing we developed a procedure using analysis of production and well-log data for identification of technogenic fracture zones and their lateral and vertical extent. The analysis of lateral technogenic fracturing distribution is based on a method of statistical evaluation of injection wells influence on production wells rates using Spearman rank correlation. According to the analysis and the results of additionally performed tracer injection test and special core analysis determining the principal stress axes on core samples we determined zones in which technogenic fracturing substantially adds to water cut of producing wells and principal directions in which fracturing takes place for each producing well. To assess the confinement of technogenic fractures to any reservoir interval we compared wells which have tight impermeable layers within productive strata and ones that lack them with fractures identified statistically. Using statistical analysis we identified for each production well the direction of fracture propagation with qualitative assessment of intensity of fracture role in fluid flow in that direction, with the preferred orientation being subparallel to low-amplitude tectonic faults coinciding with the principal directions of the stress tensor determined on core samples. A joint analysis of technogenic fracture map and distribution of tight non-permeable layers within producing intervals allowed to determine a strong correlation (central northern part of the reservoir) between the lack of these tight layers and low Spearman rank correlation coefficient, which indirectly points to the relation between tight, conductive layers (as a result of plastic deformation and subsequent fracturing) and high fluid flow rates. Analysis of production data using this algorithm helps in determination of lateral and vertical fracture distribution for subsequent analysis and alteration of waterflooding system as well as correction of injection profile, risk reduction in determination of remaining mobile oil reserves areas and planning of new wells based on realistic fluid flow models.

Numerical investigation of limitations and assumptions of analytical transient flow models in tight oil reservoirs