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Shammam, F. O. (Missouri University of Science and Technology) | Alkinani, H. H. (Missouri University of Science and Technology) | Al-Hameedi, A. T. (Missouri University of Science and Technology / American University of Ras Al Khaimah) | Dunn-Norman, S. (Missouri University of Science and Technology) | Al-Alwani, M. A. (Missouri University of Science and Technology)
Abstract Over the past decade, the oil industry witnessed an expansion in the refracturing activates instead of drilling and fracturing new wells. This work aims to test the efficiency of the refracturing treatments by analyzing the post refracturing production trend of wells in the most active shale plays in the United States (Bakken, Niobrara, Marcellus, Permian, Eagle Ford, Barnett, and Haynesville). FracFocus was used to collect data of more than 130,000 wells in the United States completed between 2012 and 2019. In this study, 39 refractured wells (Barnett wells were vertical, Niobrara wells were deviated, and the other shale plays were horizontal) in the created database were further processed by adding their production data to analyze the production data of the refractured wells and test the efficiency of refracturing as a stimulation technique to increase production. In terms of production gain, the results showed that the selected wells in the Eagle Ford shale play yielded the highest production gain from refracturing with a 174% increase of production post refracturing followed by Bakken (160%), Marcellus (133%), Barnett (46%), Niobrara (43%), Haynesville (34%), and Permian (32%), respectively. Overall, the highest production gain from refracturing is achieved during the second month after refracturing and the decrease of production gain starts during the third month after refracturing. On the other hand, the results showed that there are more factors than formation type and perforation length that need to be considered to predict the production response of refracturing as some wells showed a high gain during the first three months after refracturing, while other wells showed a lower production gain during the first three months after refracturing. Moreover, the refracturing operations have shown a production increase in vertical, deviated, and horizontal wells. Introduction Since the oil price drop in 2011, refracturing old wells and producing from shale reserves have become a new trend in the oil industry in the United States. Refracturing operations aim to maximize production through refracturing old fractured wells (Jacobs, 2015). The technology itself is not new and it has been known and active in the United States since the 1970s. However, the process of refracturing horizontally drilled multi-staged wells is a new technology that started to appear in the industry back in 2011 (Dutta, 2017). Since the oil price drop in 2011, refracturing shale reserves started to emerge in the industry due to the size of the unconventional reserves and the economic viability of producing through refracturing (King, 2014). To highlight the economic efficiency of refracturing, when comparing the cost of refracturing an existent well and fracturing a new well in the Eagle Ford, it was found that the cost of producing through a refracture is 1 to 1.5 million dollars, while the profit of producing through a new fracture is estimated to be 2 to 4 million dollars (Fu et al., 2017). Refracturing operations have some drawdowns associated with the availability of data on the surface and their rate of success is determined by many factors (Yanfang & Salehi, 2014). Therefore, it is important to consider all the associated factors of success of a refracturing operation and include a refrac plan in the initial stage of the well development phase to get a high return of investment in a short period (Dutta, 2017). One of the main factors of the refracturing operation success is the formation of the refrac. The refracture formation depends on the pressure distribution around the pre-existent fracture and the cluster spacing between the fracture stages. In some cases, a new fracture would be initiated and reaching more of the un-depleted spots in the reservoir, which dramatically increases the production of the well. However, in other cases, the refracture would be initiated through reopening the initial fracture (Fu et al., 2017). All these factors contributing to the refracture formation can lead to a high level of uncertainty that requires an intensive analysis of data before starting a refracturing operation.
Rosenhagen, Nicolas M. (Colorado School of Mines) | Nash, Steven D. (Anadarko Petroleum Corporation) | Dobbs, Walter C. (Anadarko Petroleum Corporation) | Tanner, Kevin V. (Anadarko Petroleum Corporation)
Abstract The volume of stimulation fluid injected during hydraulic fracturing is a key performance driver in the horizontal development of the Niobrara formation in the Denver-Julesburg (DJ) Basin, Colorado. Oil production per well generally increases with stimulation fluid volume. Often, operators normalize both production and fluid volume based on stimulated lateral length and investigate relationships using "per-ft" variables. However, data from well-based approaches commonly display such wide distributions that no useful relationships can be inferred. To improve data correlations, multivariate analysis normalizes for parameters such as thermal maturity, depth, depletion, proppant intensity, drawdown, geology and completion design. Although advancements in computing power have decreased cycle times for multivariate analysis, preparing a clean dataset for thousands of wells remains challenging. A proposed analytical method using publicly available data allows interpreters to see through the noise and find informative correlations. Using a data set of over 5000 wells, we aggregate cumulative oil production and stimulation fluid volumes to a per-section basis then normalize by hydrocarbon pore volume (HCPV) per section. Dimensionless section-level Cumulative Oil versus Stimulation Fluid Plots ("Normalization" or "N-Plot") present data distributions sufficiently well-defined to provide an interpretation and design basis of well spacing and stimulation fluid volumes for multi-well development. When coupled with geologic characterization, the trends guide further refinement of development optimization and well performance predictions. Two example applications using the N-Plot are introduced. The first involves construction of predictive production models and associated evaluation of alternative development scenarios with different combinations of well spacing and completion fluid intensity. The second involves "just-in-time" modification of fluid intensity for drilled but uncompleted wells (DUC's) to optimize cost-forward project economics in an evolving commodity price environment.
Summary Calcite forms variable proportions of source-rock reservoirs ("shale plays"). Although calcite content can be quantified via petrophysical analyses, XRD, XRF and other techniques, the amount of calcite, by itself, is not enough information to predict the likely importance of these minerals for reservoir and completions quality. Four principle types of calcite can be recognized:Pelagic components, mostly foraminifera and coccoliths, form a large component of the Eagle Ford and Niobrara but other types of pelagic carbonates (e.g., tentaculitids) are common in Paleozoic source-rock plays such as the Marcellus, Carbonate "event beds" (turbidites, storm deposits, etc.) are present in the Avalon, Barnett, Vaca Muerta and other plays, In situ benthic carbonates (bivalves, corals) are present in some plays (e.g., Eagle Ford, Marcellus), and Diagenetic calcites (pore filling cements, fracture fills, replacements, etc.) are present to varying degrees in perhaps most source-rock plays. Detailed core descriptions and petrographic observations are critical for assessing the origin of the calcite. Similar concepts apply to other mineral and organic components of mudstones.