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Free data from the first Permian Hydraulic Fracturing Test Site is available online and reports from the second test site will be available this summer. Those reports offer a unique look at fracturing in the Midland and Delaware Basins, using nearly every diagnostic test an engineer can think of and analysis by technology leaders including Occidental and Shell among the partners. Because the US government shares the cost with industry partners, the data are made publicly available after a period during which the companies that pay half the cost have exclusive access to it. The data posted draw on work begun more than 5 years ago. It is available on the National Energy Technology Laboratory's EDX data sharing site (details below). The files offer processed data from testing done at an 11-well pad in the Midland Basin dating back to 2015, said Gary Covatch, a petroleum engineer at the US Department of Energy.
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
Many operators have increasingly moved toward cube development to avoid production impairment due to parent and child wells’ fracture-driven interactions (FDI). This cube development technique involves stimulating multiple wells in a section before bringing them online simultaneously or relatively close in time. This implies significant upfront investment to drill and complete in some cases 10’s of wells before producing a drop of hydrocarbon from them. Therefore, it becomes critical that the wells are completed optimally to be able to extract maximum resource from the reservoir. Multi-well stacked pad development renders itself as a 4D problem for completion optimization. Well spacing in horizontal and vertical direction and perforation spacing along the lateral being the 3 spatial dimensions, as well as the timing and sequencing of stages add the fourth dimension to the problem. Sensitizing for different sequencing scenarios in the modeling space before operational execution of the stimulation offers a cost-effective way to optimize production.
We explore the impact of hydraulic fracturing sequence and spacing on production from the group of stacked wells in a section of the Delaware Basin. A three-dimensional geomodel along with a discrete fracture network is utilized to model a complex hydraulic fracture system created for multiple treatment sequencing and spacing scenarios. Stress shadow from previously stimulated stages is seen to be a major driver in controlling the geometry of the fractures in the wells stimulated later and can be utilized to enhance reservoir contact. Finite element modeling shows the positive impact of the stress re-orientation resulting from previously stimulated stages. Hydraulic fractures confined by stress from outside wells show clear growth pattern into unstimulated sections of the reservoir, thus enhancing the production potential.
The stimulated reservoir volume and simulated production are used as key performance indicators (KPIs) for choosing the optimum sequencing and spacing strategy in this study, however the KPI can be changed to meet individual asset needs. This work aims to provide a workflow for modeling stacked well pad development and explores innovative approaches to sequence stimulation stages on wells in order to improve reservoir contact.
Zhang, Zhishuai (Chevron Energy Technology Company) | Fang, Zijun (Chevron Energy Technology Company) | Stefani, Joe (Chevron Energy Technology Company) | DiSiena, James (Chevron Energy Technology Company) | Bevc, Dimitri (Chevron Energy Technology Company) | Ning, Ivan Lim Chen (Chevron Energy Technology Company) | Hughes, Kelly (Chevron Energy Technology Company) | Tan, Yunhui (Chevron Energy Technology Company)
Fiber Optic Sensing, including both low-frequency Distributed Acoustic Sensing (DAS) and Distributed Strain Sensing (DSS), can be used to record strain rate or strain for hydraulic fracturing monitoring in an offset well. However, current work focusses on acquisition, processing, and qualitative interpretation. We investigated the modeling of DAS and DSS strain responses to hydraulic fractures during stimulation process. The modeling work provides valuable insights to understand low-frequency DAS and DSS strain measurements during hydraulic stimulation.
We used the Displacement Discontinuity Method (DDM) to model the strain/strain rate field around kinematic propagating fractures. This efficient method provides a quick assessment of models with various fracture extents and net pressures. It also allows simulating the strain responses to a network of fractures in consideration of their interactions. During the stimulation stage of hydraulic treatment, the fracture propagation is modeled by prescribing gradually increased fracture size and calculating the displacement discontinuities that representing fractures at each step. After the stimulation stops, we assume the fracture extent will not change but the net pressure within the fracture gradually decreases due to fluid leakoff. We calculate the displacement discontinuities representing fractures using the fracture extent and the stress boundary conditions on fractures. The strain and stress projected along the monitoring well are calculated from these displacement discontinuities at each time step and converted to strain rate by taking their time derivatives.
We compared and verified our modeling with field observations from the Hydraulic Fracturing Test Site 2 (HFTS2) project, a research experiment performed in the Delaware Basin, West Texas. For a horizontal monitoring well, modeling results explain heart-shaped extending pattern before a fracture hit, polarity flip during stimulation due to fracture interaction, and V-shape patterns when a fracture bypasses the monitoring well from above or below without intersecting. For a vertical monitoring well, modeling shows the different characters of low-frequency DAS and DSS responses when a fracture is near and far away from a vertical monitoring well for both elliptic fractures and layered fractures.
Geomechanical modeling lays the groundwork for quantitative interpretation and fracture-geometry estimation. Our modeling approach provides insight into unraveling the patterns observed by far-field low-frequency DAS and DSS during hydraulic fracturing. Synthetic modeling results of various scenarios can also be used to improve fiber-optic acquisition design for stimulation monitoring.
Low-frequency DAS and DSS modeling and monitoring integrate information on geomechanics, fluid flow, pressure distribution, earth properties, and fracture propagation. The modeling results and field observations can also be compared and validated with engineering data such as pressure and temperature, with geological data such as cores, and with geophysics data such as microseismic and time-lapse seismic, to provide a comprehensive understanding of hydraulic fractures.
One of the missing pieces for the Delaware Basin development in the Wolfcamp Formation is optimal spacing for horizontal wells. The spacing varies with formation characteristics (rock and fluid) across the Delaware Basin. A single method of determining optimal spacing has yet to be found as many pieces of information are still missing. Among the various parameters affecting development, well patterns and completion methodologies. Both parameters show a significant impact on the drainage area of wells and may in turn affect optimal spacing between the wells. The model outcomes are expected to improve recovery efficiency and minimize environmental effects of unconventional resource development. Several spacing tests were implemented in various areas of the Delaware Basin with multiple completion strategies. Private production and spacing data were analyzed in conjunction with data analytics. This step led to a newly developed model to optimize spacing. Various reservoir parameters such as permeability, fracture width and height, drainage area, reserves, and recovery factors were estimated according to patterns discovered by transient flow rate analysis.
These parameters may lead to an optimal spacing for the stacked Delaware Basin, and contribute to a better understanding of future neighboring wells development. Our findings and correlation within the Wolfcamp will be applied to various sections and formations across the Permian Basin. Current workflows and spacing advisors require use of numerical reservoir simulation and fracture simulation. Drainage area, reserves, recovery factors, and fracture height and width are the main unknowns in unconventional plays. Application of data analytics with production, spacing, life of the well on production, and completion data is anticipated to resolve some of these issues.
The paper is to develop a thorough understanding of well spacing and to propose a strategy for optimization in shale and tight rocks. Well interference due to fracture driven interaction (FDIs) (frac hits) may occur between neighboring wells especially if the distance between the wells are narrow. This interference must be avoided to reduce negative impact on productivity and estimated ultimate recovery (EUR) of the producing wells. The impact of these interactions is intricate and requires advanced numerical modeling to account for fracture propagation and depletion effects due to varied spacing sets (Kan et al. 2019).
This study uses a machine learning framework to systematically analyze field production and completion data to understand the impact of frac-hits on parent and child wells and predict well spacing and completions design. Frac hits are one of the most pressing reservoir management issue that can enhance or compromise production over either the short-term or have sustained impacts over longer times. The extent of the impact is dictated by a complex interplay of petrophysical properties (high-perm streaks, mineralogy, etc.), geomechanical properties (near-field and far-field stresses, brittleness, etc.), completion parameters (stage length, cluster spacing, pumping rate, fluid and proppant amount, etc.) and development decisions (well spacing, well scheduling, etc.). As a result, the impact of frac-hits is not straightforward and difficult to predict.
The study uses data from the Meramec, Woodford and Wolfcamp formations. We develop an automated machine-learning based frac-hit detection algorithm that also quantifies the impact on the parent and child wells using matched decline curve models. We analyze about 500 parent and over 1100 child wells in the three formations. Our results show that the key factors governing the extent of the impact are the extent of depletion and producing oil rate of the parent well before frac hit, completion design parameters (fluid and proppant amount) and well spacing. Our machine learning analysis generates regression models to predict the impact of frac hits. These regression models are coupled with economic analysis to determine optimum spacing for any given completion design or optimum completion design for any given spacing.
The parent wells in all three formations had both positive and negative impact of the frac hits. Around 60–67% parent wells were negatively impacted while 33–40% wells were positively impacted. For the child wells, 71–85% wells were negatively impacted and 15–29% of the wells were positively impacted. Combining the impact on parent and child wells, the impact is dominated by the child wells as 69 to 82% of the parent-child pairs were negatively impacted and only 18–31% of the pairs were positively impacted. Considering percent loss in cumulative oil volumes in the next 5-years, in the Meramec, parent wells on average show a 16% reduction while child wells show a 39% reduction due to frac hits. The corresponding numbers for the Woodford formation are 19% and 37% and Wolfcamp formation are 20% and 22%, respectively. This translates to a parent well losing on average 40–50 thousand bbls in next five years and a child well losing on average 130–150 thousand bbls in the same period.
This study systematically analyzes available data to understand the impact of frac hits and formulates a machine learning-based well spacing-well completions matrix workflow that can easily be extended to other formations by integrating commonly available production and completions data.
Abivin, Patrice (Schlumberger) | Vidma, Konstantin (Schlumberger) | Xu, Tao (Schlumberger) | Boumessouer, Wissam (Schlumberger) | Bailhy, Jason (Schlumberger) | Ejofodomi, Efe (Schlumberger) | Sharma, Amit (Schlumberger) | Menasria, Samir (Schlumberger) | Makarychev-Mikhailov, Sergey (Schlumberger)
Infill drilling consists of adding horizontal wells between existing wells to optimize drainage in high-value acreage. New wells are sometimes drilled as close as 250 ft to producing or depleted wells. Fracturing the new wells creates a high risk of fracture-driven interactions (FDI). This paper describes a methodology to characterize well interference on production in unconventional basins and the impact of mitigation technologies.
Data mining, correlations, and statistical tools were developed to extract and analyze a large commercial production database covering major plays in the US. First, cloud-based algorithms were developed to identify and characterize infill wells based on coordinates, well deviations, production dates, and an adjustable radius of interference. Second, monitoring algorithms automatically captured and analyzed abrupt changes in normalized production of infill wells and neighboring wells at the time of infill well stimulation. Finally, the effect on production of both parent and child is immediately displayed on a user-friendly user interface for further visualization and interpretation.
The method was successfully applied to areas experiencing high infill drilling in major basins such as the Williston basin. Results show that production data correlate with historical changes in infill drilling density and fracturing job volumes (proppant and fluid). The production of child wells is then compared to that of their closest parent, which shows some decline as a function of the distance between wells. The systematic workflow also identifies if the basin is prone to positive fracture hits or if there is a significant decrease in the production of existing (parent) wells. The use and impact of diversion technologies as a well interference mitigation method is also studied.
These results give important insights into the effect of field development strategies on well interference and enable recommendations related to well spacing, fracturing designs, and use of fracture geometry control technologies to optimize future well and field development. Production data analysis clearly shows a beneficial impact of both near-wellbore and far-field diversion technologies on production.
Abstract The combination of extended-length horizontal drilling and high volume hydraulic fracturing has led to previously unimaginable production increases, yet the recovery potential of unconventional oil and gas resources remains largely unrealized. Recovery factors for unconventional oil and gas wells are typically reported at < 20% in gas shale reservoirs and < 10% in the oil plays. Neutrally buoyant ultra-lightweight proppants have been demonstrated to effectively provide production from fracture area that is otherwise unpropped and thus, non-contributive with conventional sand/slickwater hydraulic fracturing processes. Production simulations illustrate that treatment designs incorporating neutrally buoyant ULW proppant treatment designs tailored for contemporary unconventional well stimulations deliver cumulative production increases of 30% to over 50% compared to the typical large volume sand/slickwater treatments. Unfortunately, production simulation results may not sufficiently lessen risk uncertainties for operators planning high-cost multi-stage horizontal stimulations. Therefore, several field trial projects using the neutrally buoyant ULW proppant in extended-length horizontal unconventional wells are currently in progress to validate the production simulations. Since the initial 4-stage fracturing stimulation incorporating neutrally buoyant ultra-lightweight proppant in 2007, deployment has occurred in fracture stimulating hundreds of oil and gas wells spanning multiple basins and reservoirs. Most of the wells are vertical or relatively short lateral wells common to asset development practices predating the unconventional shale completions mania, but many were targeted at the same unconventional reservoirs as the current multi-stage horizontal completions. Several published case histories have documented the production enhancement benefits afforded by the legacy ULW proppant wells, but questions remained as to how those lessons might be correlated to provide engineers confidence in the current production simulations. Well completion and production information was mined from the various accessible databases for the neutrally buoyant ULW proppant wells. The scope of the legacy data compiled for analysis was limited to the reservoirs common to the current field trials and production simulations, ie. unconventional oil and gas shale reservoirs. Production performance contributions of neutrally buoyant ULW proppant in past applications were compared with the production uplift observed in applications and/or simulated application of neutrally buoyant ultra-lightweight proppant fracturing treatments in current multi-stage horizontal reservoirs. The lessons learned from this investigation provide the practicing engineer the means to confidently assess production simulation data for multi-stage horizontal unconventional completions incorporating neutrally buoyant ulw proppant in the treatment designs.
Ursell, Luke (Biota Technology) | Hale, Michael (Novo Oil & Gas LLC) | Menendez, Eli (Novo Oil & Gas LLC) | Zimmerman, John (Novo Oil & Gas LLC) | Dombroski, Brian (Novo Oil & Gas LLC) | Hoover, Kyle (Novo Oil & Gas LLC) | Everman, Zach (Novo Oil & Gas LLC) | Liu, Joanne (Biota Technology) | Shojaei, Hasan (Biota Technology) | Percak-Dennett, Elizabeth (Biota Technology) | Ishoey, Thomas (Biota Technology)
Abstract Subsurface DNA is an emerging independent diagnostic offering oil and gas operators a high resolution and non-invasive measurement of fluid movement in the subsurface. DNA sequencing methodologies that use subsurface DNA markers acquired from well cuttings and produced fluids are being increasingly used in the Permian Basin to elucidate drainage heights for new and existing wells with increased temporal and spatial resolution. Drainage height estimates are applied across the asset lifecycle during appraisal, development, and production. We present a new exploratory application for DNA Diagnostics in the Midland Basin as a complementary data set for understanding reservoir characteristics when existing wells and data are not available. In this work, Novo Oil and Gas and Biota Technology performed a study on an exploratory well in the Meramec formation of Ector County. Well cuttings were collected from a pilot hole to create a vertical DNA baseline through key Barnett and Meramec formations, and from a lateral section to estimate per stage oil and water contribution. Frac fluid was collected during completion and produced fluids were collected through the initial 189 days of production. A data science-based workflow was performed that tracked DNA markers within produced fluids and compared them to a well-cutting derived DNA baseline to estimate per-formation and per-stage contributions in the vertical and lateral sections, respectively. DNA Diagnostic results were integrated into a reservoir engineering workflow through comparisons with petrophysical logs, core data, geosteering reports, completions reports, production data, and oil tracers. Results showed that initial drainage heights covered a large portion of the Barnett into Woodford formations and corresponded to the higher initial production values. Over time, the DNA drainage heights indicated a focused zone of contribution from the Barnett which corresponded to a steady, flat decline curve. Lateral DNA contributions estimates indicated the highest production contribution from a section of the lateral drilled within the intended landing zone towards the toe, which was corroborated with conventional oil-based chemical tracers. Additionally, the lateral DNA Stratigraphy plots allowed for the development of a hypothesis of a potential fault encountered in the lateral, which subsequent wells will investigate. Overall, we demonstrate that Subsurface DNA Diagnostics provides an independent workflow to estimate drainage height and lateral production allocation by analyzing DNA markers acquired from cuttings and produced fluids. This work shows the complementary nature of incorporating DNA Diagnostics into traditional reservoir engineering workflows as a hypothesis generating tool and as a corroborative measurement. The scalability and non-invasive nature of the workflow has the potential to improve initial characterization and operations during field development, particularly exploratory areas with less operational history. DNA Diagnostics provided direct economic benefit to Novo's field development plan and informed subsequent capital allocation strategies.
Abstract A new approach is proposed to quantify the communication between wells in a tight multi-layered shale gas reservoir. In this approach, a wide range of data sets, from microseismic monitoring to the production data are analyzed to evaluate the communication between wells in every stage of well development. The results provide new insight into how the initial well communication during stimulation impacts the well interference during production. Microseismic data collected during hydraulic fracturing are analyzed for a three-well pad drilled in the Appalachian basin. The microseismic event locations, magnitudes, and fracture plane characteristics are used to construct a discrete fracture network (DFN). The permeability of a numerical reservoir model is calculated from the generated DFN, and the model is further integrated with available reservoir data. History matching is carried out using three years of production data to calibrate the reservoir model, which was also used to predict water and gas production for thirty years. Finally, decline curve analysis (DCA) is used to examine the production behavior of the reservoir. The microseismic data monitored during hydraulic fracturing show the presence of communication between wells in the pad. This communication, also known as frac hits, is established as more events are recorded in the offset wells, indicating the extent of hydraulic fractures. In addition, the pressure perturbation in the offset wells confirms the presence of a pathway connecting the wells during stimulation. Furthermore, the reservoir model built in the numerical reservoir simulator shows overlap of drainage volumes. In the reservoir model, the depleted region expands across multilayer formations in both lateral and vertical directions. An analysis of the production behavior of the wells using DCA suggests an almost logarithmic trend which is expected for these types of reservoirs. Surprisingly, detailed analysis of the results reveals there is no significant deviation in the overall performance of wells associated with well interference, especially in the early years of production. However, at greater than 10 years of production, the expansion of the depleted zone accelerates the well interference which leads to lower performance of the pad in the long term. The results demonstrate that the enhanced permeability zones created due to frac hits may not have an immediate impact on production performance. Traditionally, frac hits and well communication were considered damaging to the reservoir production. However, this new result shows that the well communication during fracturing may not impact short-term production. Additionally, it highlights the importance of a thorough examination of the fracture network along with the reservoir properties to evaluate the potential impact of frac hits on reservoir production.