|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
To achieve credible engineering estimates of fracture geometry, fluid efficiency, and potential risks of premature screen-out, the engineer must reliably history match the observed net-fracturing pressure. Measurement of net-fracturing pressure requires first, and foremost, a reliable estimate of the formation closure stress, to which the net pressure is referred.
This paper documents both the theory and several example field applications of a novel flow-pulse closure stress determination method. The flow-pulse technique requires only small changes in fracture treatment pumping schedule that can be accomplished at little to no extra cost, yet it allows a robust estimation of formation closure stress in real time. The flow-pulse technique involves pumping a small minifrac (usually with water) and then pumping small pulses (of about 5 bbl) of fluid during the pressure decline. There is a dramatic change in pressure response when flow pulses are pumped into an open fracture vs. a fracture that is already closed.
After a brief, but disappointing, romance with purely theoretical fracture models, the industry has now acknowledged the central role of actual measured treatment data in any serious fracture analysis effort. A large segment of the industry, however, continues to use either vastly over-simplified models (mostly 2D) or denies the value of fracture analysis altogether by simply using empirically derived fracture treatment designs and procedures. A common, however mistaken, justification for the latter two approaches is that it is simply not feasible to gather the necessary data for serious (3D, real-data) fracture analysis. This paper attempts partially to address this concern with feasible data collection for real-data fracture analysis.
Real-data fracturing analysis requires the determination of the actual observed net-fracturing pressure during a fracturing treatment and then running a suitably flexible physical model of the fracturing process until the model-predicted net-fracturing pressure matches the observed net-fracturing pressure.
Eltaleb, I. (University of Houston) | Rezaei, A. (University of Houston) | Siddiqui, F. (University of Houston) | Awad, M. M. (University of Houston) | Mansi, M. (University of Houston) | Dindoruk, B. (University of Houston) | Soliman, M. Y. (University of Houston)
The fracture injection fall-off test is a common technique for determining rock properties and fracture closure pressure. Conventional methods for analyzing DFIT are formulated based on the assumption of a vertical well and have shortcomings in horizontal wells drilled in ultra-low permeability reservoirs with potential multiple closures. In this study, an alternate technique using the signal processing approach is proposed. In the proposed method, we analyze the energy of the noise in the signal using a wavelet transform to identify the closure moment and pressure. We hypothesize that after the complete fracture closure moment, the noise in the recorded pressure will begin to vanish. To determine this closure moment, we decompose the pressure fall-off (signal) into multiple levels with different frequencies using the wavelet transform. Multiresolution wavelet decomposition breaks the (pressure) signal into high pass (noise) and low pass (approximation) components at various levels. The energy distribution plot is then constructed by plotting the energy of the high pass (noise) component versus the corresponding decomposition level.
Our results show that the noise energy reduces by several orders of magnitude at a specific time, which may identify the moment of fracture closure. Four field cases are analyzed using the proposed approach for demonstration. Also, we show an example where identifying the closure pressure using G-function is challenging, and our method still works reasonably well. Plots of the noise energy distribution versus time indicated multiple decreasing levels of energy. We also observed that the energy of the recorded noise in the signal could stay constant, or it can decrease gradually until the closure moment. In both cases, we observed that the signal energy drops to a minimum level at closure, and stays at that lowest level, thereby confirming our hypothesis. We also noted that the closure points that are found using this approach could happen before or after the closure from the conventional G-function method.
The main advantage of our proposed approach is that, unlike other physics-based techniques, it does not have any pre-assumption about the geometry of fracture or type of the well. It solely relies on the pressure signal that is recorded during the fall-off period. This advantage makes our approach unique since it is not limited to any specific formation, rock, or well type.
Abstract This paper provides a framework for adding after-closure fracturing-pressure analysis to the pre-treatment calibration-testing sequence that defines fracture geometry and fluid loss characteristics. The after-closure period contains the reservoir pseudo-linear flow period that is the focus of this paper and the pseudo-radial flow period that has been previously addressed in a comprehensive manner. Considerations beyond linear-flow include the transition from linear-flow to radial-flow that permits extracting the fracture length; the synergy and validation provided by the various phases of a fracture calibration sequence; and application examples for a large range of reservoir parameters and conditions. The examples include a summary of the operational considerations and derived benefits obtained by extensive use of the analysis offshore Trinidad during a frac-and-pack campaign, and the paper concludes with a detailed analysis of the pumping, closing, and after-closure periods for a calibration ("minifrac") treatment during this campaign. A companion paper provides a detailed analytical-framework for the after-closure period. Reservoir linear-flow provides the remaining and missing link for the fracturing-pressure chain-of-events. This chain gives a continuum of increasing information about the fracture geometry, fracturing fluid, and reservoir with feedback to validate or question prior information. The proposed timeline of events (and information) begins with a small-volume injection (for closure pressure) and shut-in (for reservoir transmissibility and initial pressure); pumping the fracture calibration treatment (for fracture geometry characteristic); the shut-in closure-decline (for total fluid-loss coefficient and fracture length to validate geometry); immediately after closure (for separating the various fluid loss mechanisms and validating closure pressure); after-closure linear-flow (for spurt-loss and to validate fracture length); and in the case of high-permeability, transitional flow (for validating various parameter-combinations) and radial-flow (for validating reservoir transmissibility and initial pressure). The ensemble of calibrated and validated information provides all the prerequisite fracture and reservoir information for achieving an on-site economics-optimized design of the proppant treatment. Introduction Figure 1 shows a typical history of the fracturing pressure from the beginning of pumping until the reservoir disturbance from the fracture decays back to the initial reservoir pressure. Of particular importance for this paper is the last period of the pressure response, or the after-closure response noted on the figure as "transient reservoir pressure near the wellbore." A calibration test is generally performed without proppant and, therefore, retains negligible conductivity when it closes. The after-closure pressure behavior is independent of the physical properties governing fracture propagation and depends only on the previous spatial and temporal history of the fluid loss, the fracture length, and the reservoir parameters. The "late-time" behavior becomes pseudo-radial flow and provides reservoir transmissibility (kh/) and initial pressure in a manner similar to more traditional methods for a well test. The after-fracture-closure application of radial-flow has been comprehensively covered in two companion papers. The first paper by Gu et al. focused on application aspects, and the second paper by Abousleiman et al. focused on theoretical aspects. The latter paper also considered approximations for the "early-time" pseudo-linear flow regime. This paper and a companion provide a similar division of focus for after-closure linear-flow. The primary role for linear-flow is to define spurt, loss and validate information available from other parts of a calibration sequence. The following sections provide illustrative examples, a cursory review of the related literature, the role of numerical simulation, an outline for incorporating after-closure and its synergy with other phases of calibration testing, and conclude with a detailed example of a combined analysis for the pumping, closure, and after-closure periods of a calibration treatment. P. 333^
Abstract A fit-for-purpose, fully coupled stress-pore pressure simulation model (Abaqus®) is used to simulate diagnostic fracture injection tests (DFITs) and generate before closure pressure responses. The simulated responses are used to explain field observations, and to propose a new concept: progressive fracture closure. The cohesive zone model (CZM) is used to model fracture propagation and closure associated with DFITs. The customized model in Abaqus® is capable of modeling all the physical processes involved in a typical DFIT including: porous media deformation? fluid flow inside the reservoir? hydraulic fracture initiation, propagation and closure? compliance change before and after closure; residual fracture conductivity? and fluid flow inside the fracture and fluid interaction between the fracture and reservoir (leakoff). A key result obtained is that the previously-introduced fracture compliance method is demonstrated to be the most reliable approach to identify fracture closure. Depending on the pressure distribution around the fracture, the closure pressure is usually found to be higher than the minimum principal stress. Based on the continuity equation, the compliance method is expanded to include the progressive fracture closure (PFC) concept. PFC refers to the scenario where fracture closure occurs gradually along the length of fracture, from the tip of the fracture to near the wellbore. Different estimates of closure pressure will be obtained early and late in this process. Several field cases are presented which exhibit progressive fracture closure. A consistent closure signature can be identified for these cases using the primary pressure derivative. This study further suggests that wellbore storage can mask the closure signature. Therefore, reducing the wellbore storage effect by using downhole shut-in makes it easier to identify fracture closure, in addition to accelerating the test. A common DFIT fracture closure referred to as "fracture height recession" is reinterpreted to be caused by the PFC phenomenon. This finding has tremendous implications for interpretation of before closure flow regimes and associated reservoir behavior. This study also confirms that the compliance method, which corresponds to fracture tip closure, provides more of a true measure of closure pressure than conventional approaches which correspond to fracture closure near the well.
This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 107877, "Holistic Fracture Diagnostics," by R.D. Barree, SPE, and V.L. Barree, Barree & Associates, and D.P. Craig, SPE, Halliburton, prepared for the 2007 SPE Rocky Mountain Oil & Gas Technology Symposium, Denver, 16-18 April. The paper has not been peer reviewed.
Since the introduction of G-function derivative analysis, prefracture-treatment diagnostic-injection tests have become a valuable and commonly used technique. Unfortunately, the technique frequently is misapplied or misinterpreted, leading to confusion and misdiagnosis of fracturing parameters. A consistent method of analysis of the G-function, its derivatives, and its relationship to other diagnostic techniques is presented.
The prefracture-treatment diagnostic-injection-test analysis provides critical input data for fracture-design models and reservoir-characterization data used to predict post-fracture production. An accurate post-treatment production forecast is necessary for economic optimization of the fracture-treatment design. Reliable results require accurate and consistent interpretation of the test data. In many cases, closure is identified mistakenly through misapplication of one or more analysis techniques. In general, a single unique closure event will satisfy all diagnostic methods. All available analysis methods should be used in concert to arrive at a consistent interpretation of fracture closure.
The relationship of the preclosure analysis to after-closure-analysis results also must be consistent. To perform the after-closure analysis correctly, the transient-flow regime must be identified correctly. Flow-regime identification has been a consistent problem in many analyses. There is no consensus regarding methods to identify reservoir-transient-flow regimes after fracture closure. The method presented in the full-length paper is not universally accepted, but it appears to fit the generally assumed model for leakoff used in most fracture simulators.
Transient-Flow Regimes During and After Fracture Closure
Immediately after shut-in, the pressure gradient along the length of the fracture dissipates in a short-duration linear-flow period. In a long fracture in low-permeability rock, the initial fracture linear flow can be followed by a bilinear-flow period, with the linear-flow transient persisting in the fracture while reservoir linear flow occurs simultaneously. After the fracture transient dissipates, the reservoir-linear-flow period can continue for some time, depending on the permeability of the reservoir and the volume of fluid stored in the fracture and subsequently leaked off during closure. After closure, the pressure transient established around the fracture propagates into the reservoir and transitions into elliptical, then pseudoradial flow. Each of these flow regimes has a characteristic appearance on various diagnostic graphs.
Fluid leakoff from a propagating fracture normally is modeled assuming 1D linear flow perpendicular to the fracture face. It has been pointed out that in some cases of moderate reservoir permeability, the linear-flow regime may not occur, even during fracture extension and early leakoff. During fracture extension and shut-in, the transient may already be in transition to elliptical or pseudoradial flow. In this case, analyses assuming a pseudolinear-flow regime will give incorrect results. In all cases, an understanding of the flow regime and its relation to the fracture geometry is critical to arriving at a consistent interpretation of the fracture falloff test.