Using Water Hammer Characteristics as a Fracture Treatment Diagnostic

Abstract

A water hammer signal is generated at the end of a hydraulic fracturing treatment from the sudden change in fluid velocity in the system. Analysis of water hammer data has been proposed to be a simple, inexpensive diagnostic technique to assess the hydraulic connection between the wellbore, fracture network, and reservoir. Previous studies have reached differing conclusions, suggesting that the water hammer signal can be dominated either by the hydraulic fracture dimensions or by wellbore effects. This study evaluates the utility of water hammer diagnostics in a large dataset to determine correlations between the observed water hammer signal and treatment size, fracture fluid type, completion type, and resulting well productivity. Optimization of hydraulic fractures requires the integration of data from a variety of sources, and water hammer data may prove to be a useful tool in a multivariate diagnostic process. This study is based on the analyses of high-frequency treatment data, post-job reports, geological data, chemical tracer results, and production from more than 100 wells completed in the Niobrara, Codell, and Wolfcamp plays. All evaluated wells were horizontal, and included cemented and uncemented wells completed with plug and perf or ball activated frac sleeves in each stage. Treatment data were sourced, compiled, and analyzed using a new frac data management software which allowed rapid identification and evaluation of water hammer signals. For each stage the water hammer signal was characterized by taking the wave period, amplitude, duration, and decay rate. Twenty-nine wells exhibiting specific water hammer characteristics were selected for more detailed analyses to evaluate the competing influence of formation parameters, completion types, and stimulation strategies on well productivity and chemical tracer recovery. Using this dataset, we reviewed the relationship between the number of perforation clusters per stage, ball-seat size, stage and cluster spacing, reservoir quality and the observed water hammer effect and productivity. The water hammer signal was found to be affected by the entire well-fracture-reservoir system. The most substantial effects on the signal are associated with the completion type and fluid system. For multistage sleeve completions, water hammer signatures were found to be less pronounced on stages near the toe of the well. Friction and other signal restrictions in the system strongly influence the amplitude of the water hammer, which is useful to assess near wellbore connection quality, fracture initiation, and fracture placement. Chemical tracer recovery in neighboring wells identified longer or more interconnected fracture networks, which also showed higher signal decay. A high signal decay rate and duration also correlate with increased well production, which we attribute to formations properties and stimulation parameters. Analyses of water hammer data are subject to limitations including signal interference introduced by pumping rate variations, fracturing fluid composition, and low sampling frequency. It is also important to consider the large frictional pressures developed in the system during pumping, especially between the wellbore and the formation, and signal attenuation in long wellbores. Therefore, it is possible that this diagnostic approach would be more applicable in wells completed with a single fracture per stage; wherein water hammer can potentially yield a more detailed understanding of fracture dynamics. This paper provides several insights and examples that will be helpful to gather and analyze water hammer data.

A diagnostic model for hydraulic fracture in naturally fractured reservoir utilising water-hammer signal

“…However, the fracture lengths estimated under the water-hammer RCI mode exceeded those calculated using alternative techniques (microseismic, electromagnetic imaging, pressure interference testing, and long-term production data analysis), although they were comparable to those derived based on microseismic stimulated reservoirs volumes and the fracture complexity index [16,17]. This is because the mechanisms of water-hammer signals and the associated characteristic parameters (R, C, and I) are complex; furthermore, they are related to factors such as the types of wells completed, the wellbore dimensions, the fluid properties, and the physical properties of the rocks surrounding the fracture [8,18,19].…”

“…A water-hammer signal is a period of pressure pulsation obtained on a surface after fracturing shut-in and contains information regarding the wellbore and hydraulic fracture. Therefore, diagnostic methods based on the wellhead waterhammer pressure are gradually highlighted owing to their cost effectiveness and simplicity [7][8][9].…”

Oscillation Times in Water Hammer Signatures: New Insights for the Evaluation of Diversion Effectiveness in Field Cases

“…A larger fracture network size would result in a higher water hammer decay. Iriarte [19] suggested that a higher decay rate was associated with increased production. The authors pointed out that additional fractures or a larger fracture network would make the water hammer decay faster.…”