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The largest natural gas producer in the US, EQT Corporation, will purchase Alta Resources Development LLC in a cash and stock deal valued at around $2.93 billion. Alta is a private-equity-backed producer led by Blackstone Group. EQT said it will pay $1 billion to Alta in cash and the rest in stock. It expects to fund the cash portion partly by drawing on its credit facilities and new debt. The deal will add around 1 billion cubic feet equivalent gas production to EQT's portfolio and is expected to be accretive to free cash flow and net asset value per share, according to the company.
Big data analytics is a big deal right now in the oil and gas industry. This emerging trend is on track to become an industry best practice for good reason: It improves exploration and production efficiency. With the help of sensors, massive amounts of data already are being extracted from exploration, drilling, and production operations, as well as being leveraged to shed light on sophisticated engineering problems. So, why shouldn't a similar approach be applied when it comes to worker health and safety; especially when it's the norm across a wide variety of other industries? While the International Association of Oil and Gas Producers came out with a safety performance report that showed fatalities and injuries for the industry were down in 2019, the US Occupational Safety and Health Administration (OSHA) says that the oil and gas industry's fatality rate is 7 times higher than all other industries in the US.
When a panel of fracturing technology leaders was asked if classic physics-based engineering matters in engineering fracturing, the answer was a qualified "sometimes." The group of three engineers speaking at the start of the SPE Hydraulic Fracturing Technology Conference was not going to dismiss the need for physics-based modeling. Still, applying the physics of flow in a complex, fractured reservoir sounded like a wrong turn. To explain further, Cameron Rempel, vice president for subsurface engineering for Occidental Petroleum, compared analysis at the fracture level to trying to understand rush hour traffic by tracking each person as they pack up in their cubicle and head for their car at the end of the day. That example, which will someday again represent office reality, is both incredibly hard to measure and analyze and does not offer a direct path to answer an analogous question that matters to oil producers: How can we measure the time it takes for all those cars to flow out of downtown and find ways to speed them up?
The submarine H. L. Hunley conducted the first successful submarine attack on an enemy vessel, USS Housatonic, during the American Civil War but was lost with all hands because of unknown circumstances. The submarine has been recovered, and recent archeological findings have uncovered that a spar torpedo was used as opposed to a standoff torpedo that was commonly assumed to have been used. As a result, the submarine would have been in close proximity to the weapon when it exploded than previously thought. A multipart investigation has been conducted with the goal of determining if this reduced standoff distance could explain the mysterious loss of the vessel in the minutes or hours after the attack. Here, the results of a bottom-up naval architectural and weapons-effects analysis are reported. Together, the experimental, computational, and analytical results provide new insight to the vessel’s stability characteristics, propulsion, and dynamic loading environment during the attack. In addition, a discussion of possible loss scenarios, informed by both calculation results and inspections of vessel’s hull, is presented. Although the story of what happened to H. L. Hunley that night remains shrouded in mystery after this work, several important new research questions emerge.
Swiss oil trader Vitol said on 30 April that its oil and gas subsidiary, Vencer Energy, was buying Hunt Oil Company's assets in the Permian Basin for an undisclosed sum. Media outlets including Bloomberg and Reuters cited sources that pegged the asking price at around $1 billion. Houston-based Vencer was established last year as the trading giant's first foray into the upstream sector. The assets include leases on 44,000 acres in the Midland Basin side of the Permian, with an output about 40,000 BOE/D. "This is an important day for Vencer as it establishes itself as a significant shale producer in the US Lower 48. We expect US oil to be an important part of global energy balances for years to come, and we believe this is an opportune time for investment into an entry platform in the Americas," said Ben Marshall, the head of Vitol's Americas business unit.
Cheniere Energy's Sabine Pass Liquefaction has supplied its first carbon-neutral cargo of liquefied natural gas (LNG) to Shell as part of the companies' long-term LNG sale and purchase agreement. The service provider worked with the oil company to offset the full life cycle greenhouse-gas emissions associated with the LNG cargo. The LNG cargo was delivered to Europe in early April. Offsets used were bought from Shell's global portfolio of nature-based projects with Cheniere purchasing the portion attributable to estimated CO2-equivalent emissions associated with activities upstream of the delivery point, including production and liquefaction. Nature-based projects protect, transform, or restore land and enable nature to add oxygen and absorb more CO2 emissions from the atmosphere.
Nicholson, A. Kirby (Pressure Diagnostics Ltd.) | Bachman, Robert C. (Pressure Diagnostics Ltd.) | Scherz, R. Yvonne (Endeavor Energy Resources) | Hawkes, Robert V. (Cordax Evaluation Technologies Inc.)
Abstract Pressure and stage volume are the least expensive and most readily available data for diagnostic analysis of hydraulic fracturing operations. Case history data from the Midland Basin is used to demonstrate how high-quality, time-synchronized pressure measurements at a treatment and an offsetting shut-in producing well can provide the necessary input to calculate fracture geometries at both wells and estimate perforation cluster efficiency at the treatment well. No special wellbore monitoring equipment is required. In summary, the methods outlined in this paper quantifies fracture geometries as compared to the more general observations of Daneshy (2020) and Haustveit et al. (2020). Pressures collected in Diagnostic Fracture Injection Tests (DFITs), select toe-stage full-scale fracture treatments, and offset observation wells are used to demonstrate a simple workflow. The pressure data combined with Volume to First Response (Vfr) at the observation well is used to create a geometry model of fracture length, width, and height estimates at the treatment well as illustrated in Figure 1. The producing fracture length of the observation well is also determined. Pressure Transient Analysis (PTA) techniques, a Perkins-Kern-Nordgren (PKN) fracture propagation model and offset well Fracture Driven Interaction (FDI) pressures are used to quantify hydraulic fracture dimensions. The PTA-derived Farfield Fracture Extension Pressure, FFEP, concept was introduced in Nicholson et al. (2019) and is summarized in Appendix B of this paper. FFEP replaces Instantaneous Shut-In Pressure, ISIP, for use in net pressure calculations. FFEP is determined and utilized in both DFITs and full-scale fracture inter-stage fall-off data. The use of the Primary Pressure Derivative (PPD) to accurately identify FFEP simplifies and speeds up the analysis, allowing for real time treatment decisions. This new technique is called Rapid-PTA. Additionally, the plotted shape and gradient of the observation-well pressure response can identify whether FDI's are hydraulic or poroelastic before a fracture stage is completed and may be used to change stage volume on the fly. Figure 1: Fracture Geometry Model with FDI Pressure Matching Case studies are presented showing the full workflow required to generate the fracture geometry model. The component inputs for the model are presented including a toe-stage DFIT, inter-stage pressure fall-off, and the FDI pressure build-up. We discuss how to optimize these hydraulic fractures in hindsight (look-back) and what might have been done in real time during the completion operations given this workflow and field-ready advanced data-handling capability. Hydraulic fracturing operations can be optimized in real time using new Rapid-PTA techniques for high quality pressure data collected on treating and observation wells. This process opens the door for more advanced geometry modeling and for rapid design changes to save costs and improve well productivity and ultimate recovery.
Abstract In this case study, we apply a novel fracture imaging and interpretation workflow to take a systematic look at hydraulic fractures captured during thorugh fracture coring at the Hydraulic Fracturing Test Site (HFTS) in Midland Basin. Digital fracture maps rendered using high resolution 3D laser scans are analyzed for fracture morphology and roughness. Analysis of hydraulic fracture faces show that the roughness varies systematically in clusters with average cluster separation of approximately 20' along the core. While isolated smooth hydraulic fractures are observed in the dataset, very rough fractures are found to be accompanied by proximal smoother fractures. Roughness distribution also helps understand the effect of stresses on fracture distribution. Locally, fracture roughness seems to vary with fracture orientations indicating possible inter-fracture stress effects. At the scale of stage lengths however, we see evidence of inter-stage stress effects. We also observe fracture morphology being strongly driven by rock properties and changes in lithology. Identified proppant distribution along the cored interval is also correlated with roughness variations and we observe strong positive correlation between proppant concentrations and fracture roughness at the local scale. Finally, based on the observed distribution of hydraulic fracture properties, we propose a conceptual spatio-temporal model of fracture propagation which can help explain the hydraulic fracture roughness distribution and ties in other observations as well.
Suarez-Rivera, Roberto (W. D. Von Gonten Laboratories) | Panse, Rohit (W. D. Von Gonten Laboratories) | Sovizi, Javad (Baker Hughes) | Dontsov, Egor (ResFrac Corporation) | LaReau, Heather (BP America Production Company, BPx Energy Inc.) | Suter, Kirke (BP America Production Company, BPx Energy Inc.) | Blose, Matthew (BP America Production Company, BPx Energy Inc.) | Hailu, Thomas (BP America Production Company, BPx Energy Inc.) | Koontz, Kyle (BP America Production Company, BPx Energy Inc.)
Abstract Predicting fracture behavior is important for well placement design and for optimizing multi-well development production. This requires the use of fracturing models that are calibrated to represent field measurements. However, because hydraulic fracture models include complex physics and uncertainties and have many variables defining these, the problem of calibrating modeling results with field responses is ill-posed. There are more model variables than can be changed than field observations to constrain these. It is always possible to find a calibrated model that reproduces the field data. However, the model is not unique and multiple matching solutions exist. The objective and scope of this work is to define a workflow for constraining these solutions and obtaining a more representative model for forecasting and optimization. We used field data from a multi-pad project in the Delaware play, with actual pump schedules, frac sequence, and time delays as used in the field, for all stages and all wells. We constructed a hydraulic fracturing model using high-confidence rock properties data and calibrated the model to field stimulation treatment data varying the two model variables with highest uncertainty: tectonic strain and average leak-off coefficient, while keeping all other model variables fixed. By reducing the number of adjusting model variables for calibration, we significantly lower the potential for over-fitting. Using an ultra-fast hydraulic fracturing simulator, we solved a global optimization problem to minimize the mismatch between the ISIPs and treatment pressures measured in the field and simulated by the model, for all the stages and all wells. This workflow helps us match the dominant ISIP trends in the field data and delivers higher confidence predictions in the regional stress. However, the uncertainty in the fracture geometry is still large. We also compared these results with traditional workflows that rely on selecting representative stages for calibration to field data. Results show that our workflow defines a better global optimum that best represents the behavior of all stages on all wells, and allows us to provide higher-confidence predictions of fracturing results for subsequent pads. We then used this higher confidence model to conduct sensitivity analysis for improving the well placement in subsequent pads and compared the results of the model predictions with the actual pad results.
ABSTRACT The industry is facing significant challenges due to the recent downturn in oil prices, particularly for the development of tight reservoirs. It is more critical than ever to 1) identify the sweet spots with less uncertainty and 2) optimize the completion-design parameters. The overall objective of this study is to quantify and compare the effects of reservoir quality and completion intensity on well productivity. We developed a supervised fuzzy clustering (SFC) algorithm to rank reservoir quality and completion intensity, and analyze their relative impacts on wells' productivity. We collected reservoir properties and completion-design parameters of 1,784 horizontal oil and gas wells completed in the Western Canadian Sedimentary Basin. Then, we used SFC to classify 1) reservoir quality represented by porosity, hydrocarbon saturation, net pay thickness and initial reservoir pressure; and 2) completion-design intensity represented by proppant concentration, number of stages and injected water volume per stage. Finally, we investigated the relative impacts of reservoir quality and completion intensity on wells' productivity in terms of first year cumulative barrel of oil equivalent (BOE). The results show that in low-quality reservoirs, wells' productivity follows reservoir quality. However, in high-quality reservoirs, the role of completion-design becomes significant, and the productivity can be deterred by inefficient completion design. The results suggest that in low-quality reservoirs, the productivity can be enhanced with less intense completion design, while in high-quality reservoirs, a more intense completion significantly enhances the productivity. Keywords Reservoir quality; completion intensity; supervised fuzzy clustering, approximate reasoning,tight reservoirs development