Extending the Effective Fracture Lengths through Mitigation of Water Trapping to Improve Eagle Ford Gas Production

Author(s):  
Luchao Jin ◽  
Blaine Spies ◽  
Shashidhar Rajagopalan
2016 ◽  
Vol 19 (03) ◽  
pp. 415-428 ◽  
Author(s):  
Najeeb S. Alharthy ◽  
Tadesse W. Teklu ◽  
Thanh N. Nguyen ◽  
Hossein Kazemi ◽  
Ramona M. Graves

Summary Understanding the mechanism of multicomponent mass transport in the nanopores of unconventional reservoirs, such as Eagle Ford, Niobrara, Woodford, and Bakken, is of great interest because it influences long-term economic development of such reservoirs. Thus, we began to examine the phase behavior and flow characteristics of multicomponent flow in primary production in nanoporous reservoirs. Besides primary recovery, our long-term objectives included enhanced oil production from such reservoirs. The first step was to evaluate the phase behavior in nanopores on the basis of pore-size distribution. This was motivated because the physical properties of hydrocarbon components are affected by wall proximity in nanopores as a result of van der Waals molecular interactions with the pore walls. For instance, critical pressure and temperature of hydrocarbon components shift to lower values as the nanopore walls become closer. In our research, we applied this kind of critical property shift to the hydrocarbon components of two Eagle Ford fluid samples. Then, we used the shifted phase characteristics in dual-porosity compositional modeling to determine the pore-to-pore flow characteristics, and, eventually, the flow behavior of hydrocarbons to the wells. In the simulation, we assigned three levels of phase behavior in the matrix and fracture pore spaces. In addition, the flow hierarchy included flow from matrix (nano-, meso-, and macropores) to macrofractures, from macrofractures to a hydraulic fracture (HF), and through the HF to the production well. From the simulation study, we determined why hydrocarbon fluids flow so effectively in ultralow-permeability shale reservoirs. The simulation also gave credence to the intuitive notion that favorable phase behavior (phase split) in the nanopores is one of the major reasons for production of commercial quantities of light oil and gas from shale reservoirs. It was determined that the implementation of confined-pore and midconfined-pore phase behavior lowers the bubblepoint pressure, and this, in turn, leads to a slightly higher oil recovery and lesser gas recovery. Also it was determined that the implementation of midconfined-pore and confined-pore phase-behavior shift reduces the retrograde liquid-condensation region, which in turn, leads to lower liquid yield while maintaining the same gas-production quantity. Finally, the important reason that we are able to produce shale reservoirs economically is “rubblizing” the reservoir matrix near HFs, which creates favorable permeability pathways to improve reservoir drainage. This is why multistage hydraulic fracturing is so critical for successful development of shale reservoirs.


2018 ◽  
Author(s):  
Nicholas J. Gianoutsos ◽  
◽  
Seth S. Haines ◽  
Brian A. Varela ◽  
Katherine J. Whidden

2020 ◽  
Vol 112 (3) ◽  
pp. 595-602
Author(s):  
David Gunn ◽  
Rajani Murthy ◽  
Giles Major ◽  
Victoria Wilkinson-Smith ◽  
Caroline Hoad ◽  
...  

ABSTRACT Background Wheat bran, nopal, and psyllium are examples of particulate, viscous and particulate, and viscous fibers, respectively, with laxative properties yet contrasting fermentability. Objectives We assessed the fermentability of these fibers in vitro and their effects on intestinal function relevant to laxation in vivo using MRI. Methods Each fiber was predigested prior to measuring gas production in vitro during 48-h anaerobic incubation with healthy fecal samples. We performed a randomized, 3-way crossover trial in 14 healthy volunteers who ingested 7.5 g fiber twice on the day prior to study initiation and once with the study test meal. Serial MRI scans obtained after fasting and hourly for 4 h following meal ingestion were used to assess small bowel water content (SBWC), colonic volumes, and T1 of the ascending colon (T1AC) as measures of colonic water. Breath samples for hydrogen analysis were obtained while patients were in the fasted state and every 30 min for 4 h following meal ingestion Results In vitro, the onset of gas production was significantly delayed with psyllium (mean ± SD: 14 ± 5 h) compared with wheat bran (6 ± 2 h, P = 0.003) and was associated with a smaller total gas volume (P = 0.01). Prefeeding all 3 fibers for 24 h was associated with an increased fasting T1AC (>75% of values >90th centile of the normal range). There was a further rise during the 4 h after psyllium (0.3 ± 0.3 s P = 0.009), a fall with wheat bran (−0.2 ± 0.2 s; P = 0.02), but no change with nopal (0.0 ± 0.1 s, P = 0.2). SBWC increased for all fibers; nopal stimulated more water than wheat bran [AUC mean (95% CI) difference: 7.1 (0.6, 13.8) L/min, P = 0.03]. Breath hydrogen rose significantly after wheat bran and nopal but not after psyllium (P < 0.0001). Conclusion Both viscous and particulate fibers are equally effective at increasing colonic T1 over a period of 24 h. Mechanisms include water trapping in the small bowel by viscous fibers and delivery of substrates to the colonic microbiota by more fermentable particulate fiber. This trial was registered at clinicaltrials.gov as NCT03263065.


Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 780
Author(s):  
Joel Holliman ◽  
Gunnar W. Schade

The recent decade’s rapid unconventional oil and gas development in the Eagle Ford of south-central Texas has caused increased hydrocarbon emissions, which we have previously analyzed using data from a Texas Commission on Environmental Quality air quality monitoring station located downwind of the shale area. Here, we expand our previous top-down emissions estimate and compare it to an estimated regional emissions maximum based on (i) individual facility permits for volatile organic compound (VOC) emissions, (ii) reported point source emissions of VOCs, (iii) traffic-related emissions, and (iv) upset emissions. This largely permit-based emissions estimate accounted, on average, for 86% of the median calculated emissions of C3-C6-hydrocarbons at the monitor. Since the measurement-based emissions encompass a smaller section of the shale than the calculated maximum permitted emissions, this strongly suggests that the actual emissions from oil and gas operations in this part of the Eagle Ford exceeded their permitted allowance. Possible explanations for the discrepancy include emissions from abandoned wells and high volumes of venting versus flaring. Using other recent observations, such as large fractions of unlit flares in the Permian shale basin, we suggest that the excessive venting of raw gas is a likely explanation. States such as Texas with significant oil gas production will need to require better accounting of emissions if they are to move towards a more sustainable energy economy.


2019 ◽  
Author(s):  
Nicholas J. Gianoutsos ◽  
◽  
Seth S. Haines ◽  
Brian A. Varela ◽  
K.J. Whidden

2015 ◽  
Author(s):  
Amir M. Nejad ◽  
Stanislav Sheludko ◽  
Robert F. Shelley ◽  
Trey Hodgson ◽  
Riley McFall

Abstract Unconventional shale resources are key hydrocarbon sources, gaining importance and popularity as hydrocarbon reservoirs both in the United States and internationally. Horizontal wellbores and multiple transverse hydraulic fracturing are instrumental factors for economical production from shale assets. Hydraulic fracturing typically represents a major component of total well completion costs, and many efforts have been made to study and investigate different strategies to improve well production and reduce costs. The focus of this paper is completion effectiveness evaluation in different parts of the Eagle Ford Shale Formation, and our objective is to identify appropriate completion strategies in the field. A data-driven neural network model is trained on the database comprised of multiple operators' well data. In this model, drilling and mud data are used as indicators for geology and reservoir-related parameters such as pressure, fluid saturation and permeability. Additionally, completion- and fracture-related parameters are also used as model inputs. Because wells are pressure managed differently, normalized oil and gas production is used as a model output. Thousands of neural networks are trained using genetic algorithm in order to fully evaluate hidden correlations within the database. This results in selection of a neural network that is able to understand reservoir, completion and frac differences between wells and identify how to improve future completion/stimulation designs. The final neural network model is successfully developed and tested on two separate data sets located in different parts of the Eagle Ford Shale oil window. Further, an additional test data set comprised of eight wells from a third field location is used to validate the predictive usefulness of the data-driven model. Under-producing wells were also identified by the model and new fracture designs were recommended to improve well productivity. This paper will be useful for understanding the effects of completion and fracture treatment designs on well productivity in the Eagle Ford. This information will help operators select more effective treatment designs, which can reduce operational costs associated with completion/fracturing and can improve oil and gas production.


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