This article focuses on interpretation of well test data from wells completed in naturally fractured reservoirs. Because of the presence of two distinct types of porous media, the assumption of homogeneous behavior is no longer valid in naturally fractured reservoirs. This article discusses two naturally fractured reservoir models, the physics governing fluid flow in these reservoirs and semilog and type curve analysis techniques for well tests in these reservoirs. Naturally fractured reservoirs are characterized by the presence of two distinct types of porous media: matrix and fracture. Because of the different fluid storage and conductivity characteristics of the matrix and fractures, these reservoirs often are called dual-porosity reservoirs.

Productivity estimates in horizontal wells are subject to more uncertainty than comparable estimates in vertical wells. Further, it is much more difficult to interpret well test data because of 3D flow geometry. The radial symmetry usually present in a vertical well does not exist. Several flow regimes can potentially occur and need to be considered in analyzing test data from horizontal wells. Wellbore storage effects can be much more significant and partial penetration and end effects commonly complicate interpretation. In vertical wells, variables such as average permeability, net vertical thickness, and skin are used. Horizontal wells need more detail. Not only is vertical thickness important, but the horizontal dimensions of the reservoir, relative to the horizontal wellbore, need to be known. Evaluation of data from a vertical wellbore will generally center on a single flow regime, such as infinite-acting radial flow, known as the MTR. However, a pressure-transient test in a horizontal well can involve as many as five major and distinct regimes that need to be identified. These regimes may or may not occur in a given test and may or may not be obscured by wellbore storage effects. Each flow regime can be modeled by an equation that can be used to estimate important reservoir properties.

Fractures are common features of many carbonate reservoirs. Given complex flow network that they create, characterization of dynamic behavior of these reservoirs is often complicated and becomes important, especially, if fractures provide primary pathways of fluid flow. In this paper a novel semianalytical simulator was used to understand the pressure behavior of naturally fractured reservoir containing a network of discrete and/or connected finite and infinite-conductivity fractures.

In this study an integrated interpretation methodology is applied to analyze well test data acquired in open hole section of exploration well drilled into highly fractured carbonate reservoir of Lower Eocene - Upper Cretaceous sediments on Patardzeuli field of Block XI-B, Republic of Georgia. The main steps consisted of explicitly modeling fractures - both wellbore-intersecting fractures and fractures located away from wellbore - using formation microimager data and calibrating the model to actual well test response using a unique novel mesh-free semi-analytical simulator designed for fractured reservoirs.

Study presents the results of well test of one zone performed in highly fractured carbonate reservoir drilled in Patardzeuli field. The pressure-transient response confirmed the complexity of reservoir and dominant contribution to flow regimes from fractures.

It is shown in this paper that there are many factors that dominate transient behavior of a well intersected by natural fractures, such as fracture conductivity, length, intensity and distribution, as well as whether fractures intersect the wellbore or not. Moreover, it was demonstrated that presence or absence of damage on wellbore-intersecting fractures in vicinity of wellbore will impact the pressure- transient behavior of reservoir and shape overall productivity of the well.

The novelty of the approach is the analysis of the dynamic behavior using a unique semi-analytical pressure transient simulator for fractured reservoirs. The simulator can be used to obtain a response for arbitrarily distributed infinite and/or finite conductivity natural fractures within the reservoir by modeling them explicitly. In this study, it allowed to maximize the value of well tests by assessing the effect of fractures on reservoir dynamic behavior and obtain matrix and fracture parameters where conventional well test interpretation tools would be deemed unviable.

This paper proposes the difference-value plotting function (DVPF) for the diagnostic analysis and interpretation of pressure transient test data in low-permeability reservoirs. Specifically, this work uses the approximation of the analytical solution for the performance of a vertical well with a single finite conductivity vertical fracture, where a Taylor Series expansion is used to obtain an asymptotic solution for early-time flow, which includes terms for wellbore storage and fracture conductivity. The well-testing derivative of this result is then obtained and is of a similar form.

By subtracting the derivative form from the pressure form, we remove the "dominant" wellbore storage term from the asymptotic solution. We then need to normalize that difference by the square root of time (or dimensionless time) to obtain the final formulation of the DVPF which leaves a single constant parameter multiplied by time on the right-hand-side. Our contention is that this formulation leaves us with a diagnostic plotting function which provides a unique and contrasting behavior compared to using the pressure drop and/or pressure drop derivative functions alone for diagnostics and interpretations.

As is typical of pressure transient or well testing data at early times, the observed pressures often exhibit random data noise. As such, we have adapted a noise reduction algorithm that was originally used for signal processing to smooth both the pressure and derivative functions.

Lastly, we demonstrate the difference-value plotting function (DVPF) on several cases of synthetic and field-derived data to illustrate the utility of this methodology. Specifically, we have applied this method to cases in which it is difficult to determine unique interpretations using traditional methods (e.g., insufficient duration tests, lengthy WBS distortion, and effects of ultra-low permeability). The proposed DVPF allows us to observe underlying characteristics that are obscured at early times in traditional pressure and derivative analysis, and for the demonstration examples provided in this work, the DVPF does provide a strong auxiliary means of interpretation.

Fractures are common features of many carbonate reservoirs. Given complex flow network that they create, characterization of dynamic behavior of these reservoirs is often complicated and becomes important, especially, if fractures provide primary pathways of fluid flow. In this paper a novel semi-analytical simulator was used to understand the pressure behavior of naturally fractured reservoir containing a network of discrete and/or connected finite and infinite-conductivity fractures.

In this study an integrated interpretation methodology is applied to analyze well test data acquired in open hole section of exploration well drilled into highly fractured carbonate reservoir of Lower Eocene – Upper Cretaceous sediments on Patardzeuli field of Block XI-B, Republic of Georgia. The main steps consisted of explicitly modeling fractures - both wellbore-intersecting fractures and fractures located away from wellbore - using formation microimager data and calibrating the model to actual well test response using a unique novel mesh-free semi-analytical simulator designed for fractured reservoirs.

Study presents the results of well test of one zone performed in highly fractured carbonate reservoir drilled in Patardzeuli field. The pressure-transient response confirmed the complexity of reservoir and dominant contribution to flow regimes from fractures.

It is shown in this paper that there are many factors that dominate transient behavior of a well intersected by natural fractures, such as fracture conductivity, length, intensity and distribution, as well as whether fractures intersect the wellbore or not. Moreover, it was demonstrated that presence or absence of damage on wellbore-intersecting fractures in vicinity of wellbore will impact the pressure-transient behavior of reservoir and shape overall productivity of the well.

The novelty of the approach is the analysis of the dynamic behavior using a unique semi-analytical pressure transient simulator for fractured reservoirs. The simulator can be used to obtain a response for arbitrarily distributed infinite and/or finite conductivity natural fractures within the reservoir by modeling them explicitly. In this study, it allowed to maximize the value of well tests by assessing the effect of fractures on reservoir dynamic behavior and obtain matrix and fracture parameters where conventional well test interpretation tools would be deemed unviable.

The diagnostic plot is a log-log plot of the pressure change and pressure derivative (vertical axis) from a pressure transient test vs. elapsed time (horizontal axis). Figure 1 shows an example of a diagnostic plot. The diagnostic plot can be divided into three time regions: early, middle, and late. At the earliest times on a plot (the early-time region), wellbore and near-wellbore effects dominate. These effects include wellbore storage, formation damage, partial penetration, phase redistribution, and stimulation (hydraulic fractures or acidization).

Type curves provide a powerful method for analyzing pressure drawdown (flow) and buildup tests. Fundamentally, type curves are preplotted solutions to the flow equations, such as the diffusivity equation, for selected types of formations and selected initial and boundary conditions. Because of the way they are plotted (usually on logarithmic coordinates), it is convenient to compare actual field data plotted on the same coordinates to the type curves. The results of this comparison frequently include qualitative and quantitative descriptions of the formation and completion properties of the tested well. The solutions plotted on type curves are usually presented in terms of dimensionless variables.

ABSTRACT The interpretation of pressure data recorded during a well test has been used for many years to evaluate reservoir characteristics. The pressure derivative has been applied as a powerful diagnostic tool in interpretation of pressure tests for a single well with wellbore storage and skin in a homogeneous reservoir. The objective of this study is to illustrate the applications of the pressure derivative plot, a) as a powerful diagnostic tool for reservoir model identification; b) to perform type-curve analysis; and, c) as a stand-alone specialized plot for evaluating basic reservoir parameters for single-well tests. The application of the pressure derivative has significantly made well test interpretation easier to perform. Also, the pressure derivative allows greater accuracy in reservoir flow parameter determination eliminating the need to perform the complementary specialized analysis. The cases from Southern Iraq reservoirs as compared with theoretical and published examples highlight their practical application in this area. This paper illustrates the advantages of the derivative approach, in obtaining a better solution to a problem, in comparison to the more traditional dimensionless pressure change type-curve and semi-log methods. 1. INTRODUCTION The analysis of pressure data recorded during a well test has traditionally been based upon the determination of straight lines drawn on plots with specific scales (Al-Rbeawi, 2018). A type curve analysis approach was introduced in the petroleum industry by Agarwal et al. (1970) as a valuable tool when used in conjunction with conventional semi-log plots. The type curve is a graphic representation of the theoretical response during a test of an interpretation model that represents the well and the reservoir being tested. For a constant-pressure test, the response is the change in production rate; for a constant-rate test, the response is the change in pressure at the bottom of the well. The type curves are derived from solutions to the flow equations under specific initial and boundary conditions. For the sake of generality, type curves are usually presented in dimensionless terms, such as a dimensionless pressure vs. a dimensionless time. A given interpretation model may yield a single type curve or one or more families of type curve, depending on the complexity of the model. The type curve analysis consists of finding a type curve that "matches" the actual response of the well and the reservoir during the test. The reservoir and well parameters, such as permeability and skin, can then be calculated from the dimensionless parameters defining that type curve. Type curves are advantageous because they may allow test interpretation even when wellbore storage distorts most or all of the test data; in that case, conventional methods fail.

ABSTRACT Currently, there is no direct method to quantify performance of a stimulation program after hydraulic fracture treatment. Stimulated Reservoir Volume (SRV) is widely used out of convenience; however, incongruities regarding SRV makes it difficult to ascertain fracture effectiveness. This paper presents a novel approach employing only production rate and pressure to derive the reservoir behavior and predict production performance to quantify hydraulic fractures using the Connected Reservoir Storage Model (CRSM), predicated on pressure diffusivity theory. The CRSM can predict the capability of a stimulation program by analyzing the normalized production rate and the normalized cumulative production. This paper proposes the utilization of the CRSM in lieu of SRV for multiple stage fracture characterization. CRSM directly characterizes the stimulation performance, only utilizing actual production which is free of subsurface uncertainties and can be used efficiently in characterizing the flow regimes and reservoir boundaries. The CRSM allows for the estimation of the efficiency of a stimulation program through production decline and reservoir pressure response from production data and is strongly physics-based. A real field shale gas production case will be used. 1. INTRODUCTION Unconventional reservoirs are reservoirs that require specialized recovery methods outside of conventional means to produce hydrocarbons efficiently and economically. The principal objective of completing unconventional reservoirs is to increase the effective surface area of the well to maximize production (Bybee 2011). Shale gas reservoirs are the focus of this study, which are usually characterized as a tight formation with very low permeability characteristics - generally on the order of 1 – 100 nd (Kim and Lee 2015). Shales contain organic content in high quantities and are the source rock as well as the reservoir. The gas is deposited in the pore space of the rock formations and some of the gas may be absorbed by the organic material within the source rock. The matrix permeabilities of shales have been an obscure characteristic to measure. As such, it is difficult to fully understand how gas migrates through the formation during production. Economic production cannot be achieved unless large conductive surface areas are created to allow for contact with the matrix, through existing complex natural fracture networks composed by natural fractures and hydraulic fractures (Warpinski et al. 2009). Currently, the physics governing shale gas reservoirs, specifically the flow characteristics in shales, is still not well understood, which poses a great challenge for accurately predicting shale gas performance. Explicit characterization of fracture networks is still an ambiguous science and cannot be determined with accurate precision; therefore, current ways to characterize fractures use direct far-field and direct near-wellbore methods, which consist of microseismic, tiltmeters, tracers, temperature logs and well testing theory (Clegg 2007). Both direct far-field and direct near-wellbore methods are respectable tools to help in the characterization of fractures; however, the technology for some of these methods is still undergoing development and may reveal diminutive information regarding the geometry of the actual factures. In addition, it should be emphasized that rock-mechanics only allows for the understanding of the likely crack-growth due to the heterogeneous nature of the rock formation and does not give meticulous characterization of a fracture (Stefik and Paulson 2011). Moreover, there are various in-direct methods in the literature that are used in direct fracture diagnosis for post-fracture well test analysis. Some classical approaches include the Gringarten type curve, (Gringarten et al. 1974), Agarwal type curve (Agarwal et al. 1979), Barker-Ramey type curve (Ramey Jr and Gringarten 1975) and Cinco-Ley type curve (Cinco et al. 1978) and many others. All these methods are used in some form to determine post-fracture analysis through constant production or bottom-hole flowing pressure, wellbore storage and have various applications in buildup and drawdown analysis. More recent developments in rate transient behavior regarding tight formations to allow for the quantification of hydraulic fracture treatment in the last decade has been conducted by (Pang et al. 2016) looking at actual to optimal designs of hydraulic fractures, numerical modeling of complex fracture patterns in tight formations (Olorode et al. 2013), trilinear flow solution to simulate pressure transient and production behaviors of fractured horizontal wells in unconventional shales (Brown et al. 2011), comprehensive studies of high performance fracture completions (Zhang et al. 2010) and comparison of fracture horizonal wells conducted by (Ozkan et al. 2011) to name just a few.

Analysis of the pressure transient data obtained during drillstem tests (DSTs) or standard well tests represents average formation properties of the entire interval open to flow below the packers. In contrast, a mini-DST performed on a wireline provides localized reservoir information in a fraction of the time taken by DSTs or standard well tests, which is demonstrated in this work when a pilot well was drilled for data acquisition purposes into a low-permeability reservoir abandoned in the early 1970s because of the tight nature of the formation. This work reevaluates the potential for further exploitation of this mature tight field.

A complete suite of conventional and advanced well logs was run to understand the reservoir. In addition, mini-DSTs and a surface shut-in well test were conducted to make the petrophysical model more reliable through integrated interpretation. Based on well logs, three depths were selected for fluid sampling and formation testing with a wireline straddle packer. Pressure buildups for the three tests were 3.5, 2.9, and 1.7 hours, respectively. Build-up time was sufficient for these three mini-DSTs to reach radial flow for proper pressure-transient analysis, with some evidence of suspected boundary effects following the end of the radial flow. After the well was completed, a 20-ft interval was perforated to conduct a full-scale surface shut-in well test planned on the same interval as the initial formation test with the wireline straddle packer. The entire well test duration was 206 hours, with 110 hours of drawdown pressure and 95 hours of usable pressure build-up data.

After analyzing the three mini-DSTs, reservoir properties (i.e., formation pressure, permeability and anisotropy, skin damage, and suspected boundary effects) were obtained. The pressure-transient data during the first pump out indicated the presence of high formation damage caused by water-based mud filtrate blocking the pores, which was reducing with production. The other two mini-DST results exhibited some layers with high permeability, although they were filled with water.

Alternatively, the analysis of the surface shut-in well test exhibited significant dominance of wellbore storage that masked the radial flow period and any boundary effects that could have been observed. However, it did provide comparable formation pressure, formation capacity (kh), and skin damage results that helped further validate the mini-DST analysis results.