Analysis of Generated and Reflected Pressure Waves during Fracturing Reveals Fracture Behavior
Bibliographic record
Abstract
Analysis of Generated and Reflected Pressure Waves during Fracturing Reveals Fracture Behavior Jim B. Surjaatmadja; Jim B. Surjaatmadja Halliburton Search for other works by this author on: This Site Google Scholar Stan Stephenson; Stan Stephenson Halliburton Search for other works by this author on: This Site Google Scholar Champak Bhaumik; Champak Bhaumik Nexen Canada Ltd. Search for other works by this author on: This Site Google Scholar Stewart Thompson; Stewart Thompson Halliburton Canada Search for other works by this author on: This Site Google Scholar Alick Cheng Alick Cheng Halliburton Canada Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, September 2002. Paper Number: SPE-77598-MS https://doi.org/10.2118/77598-MS Published: September 29 2002 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Surjaatmadja, Jim B., Stephenson, Stan, Bhaumik, Champak, Thompson, Stewart, and Alick Cheng. "Analysis of Generated and Reflected Pressure Waves during Fracturing Reveals Fracture Behavior." Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, September 2002. doi: https://doi.org/10.2118/77598-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Annual Technical Conference and Exhibition Search Advanced Search AbstractFracture behavior is an important aspect in fracturing technology. Many techniques are available for prestimulation simulations and post-stimulation analysis of fracture behavior. However, very few techniques address fracture behavior during the stimulation process itself. Various fracture behaviors, such as fracture extension, ballooning, and tip screenout are often not known to the operator until after it is too late or even after the job is completed. Therefore, it is important to create and evaluate different real-time analysis techniques that can be used to capture the critical information available from data gathered during jobs.During the stimulation process, many types of information are available to the engineer. Pressure, flow, and temperature are basic information evaluated by many in the past. However, surface-pressure measurements are heavily influenced by friction, densities, proppant concentrations, and flow fluctuations, which makes conventional analyses difficult, if not impossible. In spite of this, analysis of dynamic pressure fluctuations has not been actively pursued. Certain changes in the downhole configuration, such as fracture extension, may send different pressure frequency spectra and wave intensities to the surface. The signature of these pressure waves is believed to carry such information to the surface. It is also believed that signal degradation due to friction may not influence the outcome of this type of analysis.Capturing and evaluating generated and reflected pressure waves during fracturing may be a new approach to monitor what happens downhole during fracturing. This paper discusses different real-time analysis approaches, such as frequency analysis and wavelet technologies, and evaluates their results and compares them to real job data. These analysis results and the successful stimulation results are presented in this paper.IntroductionStimulating wells that behave nicely (e.g., wells that are easily stimulated) allows service companies and operators to follow standard procedures commonly performed on such wells. No special attention needs to be placed upon specifics, such as how the fracture behaves; all decisions and actions are based upon the experience the industry has acquired in the last five decades.1However, as the hydrocarbon supply decreases and demand for it increases, the hunt for hydrocarbons becomes more challenging. New technologies, such as fluid chemistry and rheology, or even new stimulation techniques enter the marketplace. These techniques claim to provide better fracture creation, better conductivities, permeability modifications, and more. As these technologies are used, new methods for evaluating the effectiveness of the treatments are needed.In the field of fracture-size development and measurement, tiltmeter technology may be one practical way to detect fracture shape and size. However, special equipment is required to capture this data and the sensitivity requirements make this process quite costly. In this paper, possible practical and economical means of observing fracture development with less elaborate schemes are investigated. Some of these methods eventually could be used for mapping the fracture in the future. Keywords: bhaumik, thompson, fracture development, surjaatmadja, hydraulic fracturing, cheng spe 77598, stephenson, upstream oil & gas, pressure wave spe 77598, annulus pressure Subjects: Hydraulic Fracturing This content is only available via PDF. 2002. Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".