|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
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
Smye, Katie M. (Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin) | Ikonnikova, Svetlana (Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas / Technical University of Munich, TUM School of Management) | Yang, Qian (Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas) | McDaid, Guin (Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas) | Goodman, Emery (Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas)
In 2018 the U.S. became the largest oil and natural gas producer in the world. Whether this production can be sustained by technologic improvements or requires more intensive completions strategies has not been determined. If the latter, improvements may be exhausted due to diminishing returns, and a slowdown in investment and development, followed by sensitivity to future economic conditions, may be observed. To address questions of production performance as a function of both reservoir properties and completion intensity, we present a comprehensive comparative analysis of four tight oil plays: the Bakken of the Williston Basin, the Eagle Ford, and the Wolfcamp A and B of the Midland and Delaware Basins. We characterize variability in geologic properties within each play and across studied plays, focusing on attributes that can be interpreted basin-wide, including depth, thickness, porosity, water saturation, and brittleness. Drilled areas with comparable variability in key geologic attributes are identified across plays, and well productivity over time in those comparable reservoir regions is compared. Well completion trends, including treatment fluid and proppant intensities over time, are investigated for these areas. We show that capturing geologic variability in porosity, water saturation, depth and brittleness index allows for comparison of productivity in "geobins." The analysis provides insight into the effectiveness of more intensive completions strategies in terms of well performance. We also show that poorer per-well productivity in some plays can be explained by well downspacing. The results of this analysis allow us to determine the geologic limitations to well productivity in oil plays through a multi-basin study, to understand whether further technological improvements may be achieved, and to predict productivity improvements due to shared technological learnings across plays.
Tight oil production in the U.S. has increased dramatically in recent years with the utilization and enhancement of horizontal drilling and hydraulic fracturing techniques, from 0.5 to over 8 million barrels (MMbbl) per day from 2005 to 2020 (Figure 1). However, the extent to which this increase in production reflects concentrated drilling in geologically attractive areas, step changes in technology, or more intensive and expensive completions strategies, has not been determined on basin-wide and multi-basin scales. To understand how drilling and completions parameters affect productivity and recovery efficiency, we seek to compare areas across plays with comparable variability in the geologic properties that can be measured and mapped, and that are likely to be the primary geologic drivers of resource-in-place and productivity.
It has long been postulated that complicated problems can usually be solved with simple solutions. While this is not always the case, one might, at least, ask for a simple framework to guide a team through a technically difficult issue. When one private oil & gas operator was faced with the common industry challenge of Parent/Child well interactions in an unconventional, dry-gas shale, a collaborative team applied a simple workflow in the form of the scientific method. The iterative workflow provided a simple approach to utilize common data, clearly calculate economic risk and ultimately reveal major performance indicators of offset well development.
The study area focuses on the northeast region of Pennsylvania, specifically in the dry gas window of the Marcellus Shale. More specifically, five counties in Pennsylvania (Bradford, Sullivan, Susquehanna, Wyoming and Lycoming) are studied after the operating company moved into full time development and started offsetting older appraisal wells. The impact from these offset events were varied ranging from parents and children losing reserves to parents and children gaining reserves. However, value loss was more common. As this risk grew, management charged the technical team and service partners with the goal of empirically mitigating offset frac interference to 1) protect the Parent well's original completion and 2) maximize a Child well's completion effectiveness.
To accomplish these goals, the team employed the scientific method to observe offset events, measure the impact to reserves and experiment with mitigation techniques. To date, the team has cataloged > 70 offset events, classified over 350 frac hits and tested one mitigation technique. In addition to an offset frac workflow, this paper will highlight statistical correlations of high value variables and detail an economic Monte Carlo Simulator to quantify the risk of a parent/child event.
Hansen, Mary (McDaniel & Associates Consultants) | Hamm, Brian (McDaniel & Associates Consultants) | Wynveen, Jared (McDaniel & Associates Consultants) | Schlosser, Tyler (McDaniel & Associates Consultants) | Jenkinson, David (McDaniel & Associates Consultants) | Dang, Hoang (McDaniel & Associates Consultants)
Abstract Unconventional reservoirs with low permeability shales and siltstones are currently being developed using horizontal wells in multiple layers. As this development technique has become more common, accurately understanding well-to-well communication is increasingly critical. Well positioning, reservoir thickness and well interference effects are important factors in the success of multi-layer development. Traditional well density metrics such as wells per section and lateral well spacing do not account for the multi-layer nature of these plays. This paper introduces readily derived metrics that enable a three-dimensional (3D) quantification of multi-layer well density. Unlike traditional analysis which considers pad development from a bird’s eye view, this paper considers the vertical cross-section of a pad which enables the 3D drainage to be quantified. The metrics Cross-Sectional Drainage Area (XDA) and Three-Dimensional Proppant Intensity (3DPI) are defined. XDA quantifies the well density relative to the thickness of the reservoir. 3DPI represents completion intensity and reservoir stimulation relative to the cubic volume of gross rock attributed to the multi-layer development. Once introduced, these two metrics are correlated to well and pad level performance. Examples from the Montney Formation in Western Canada and the Bakken Formation in North Dakota, USA are studied in detail. Ultimate hydrocarbon recovery factors, early time well performance and production profiles are analyzed and compared to the XDA and 3DPI metrics using visual analytics and multivariate machine learning models. In both the Montney and Bakken examples, XDA correlates with well performance and 3DPI correlates with pad hydrocarbon recovery factors.
Cao, Richard (Shell Exploration and Production Co.) | Chen, Chaohui (Shell International Exploration and Production Inc.) | Li, Ruijian (Shell Exploration and Production Co.) | Firincioglu, Tuba (Nitec LLC) | Ozgen, Chet (Nitec LLC) | Croft, Tyler (Shell Exploration and Production Co.) | Kathel, Prateek (Shell Exploration and Production Co.) | Girardi, Alejandro (Shell Exploration and Production Co.) | Chowdhury, Nitin (Shell Exploration and Production Co.)
Summary Appropriate well spacing decision is critical for unconventional asset development. Operators generally use three methods to identify optimum well spacing: trial and error, pilots, and modeling. The field trials and pilots often involve significant capital investment and require significant time before conclusive results can be observed. On the other hand, modeling is cost effective and time efficient but has large uncertainties in the results, which must be carefully calibrated with the field measurements to narrow down the uncertainty range. In this paper, these three methods are systematically integrated to study well interference and identify optimum well spacing for Wolfcamp development at Delaware basin. First, multiple well spacing pilots are drilled and produced with various diagnostic signals collected, such as Microseismic, Bottom Hole Pressure (BHP), fluid sampling, etc. Then the general production trend analysis is performed for these pilot results combined with other available public data from the Delaware basin. After that, a well spacing trial with good quality of data is selected as the modeling target. A full-scale 3D multi-well reservoir model with geomechanical effects was built for history match of the oil, gas, water productions, and pressure. The modeling results are carefully calibrated with the field data at different time and length scales. The potential production interference of different well spacing is captured as Estimated Ultimate Recovery (EUR) reduction compared to the base case. At the same time, stochastic studies with hundreds of simulation runs are performed on a simple reservoir model to investigate the impacts of production of interference for different well spacing and subsurface parameters. The results show that the production interference among horizontal wells have large uncertainty due to the heterogeneous subsurface parameters and the hydraulic fracturing process. The EUR reduction correlations obtained from this workflow then integrate with economic criteria (i.e. capital efficiency, Net Present Value (NPV), and cash flow) to determine the optimum well spacing.
Pradhan, Yogashri (Texas Oil and Gas Institute) | Xiong, Hongjie (Texas Oil and Gas Institute) | Forrest, James (Texas Oil and Gas Institute) | Zhu, Jane (Texas Oil and Gas Institute) | Spath, Jeff (Texas Oil and Gas Institute)
Abstract University Lands' production and revenue are driven by over 270 operators in the Midland and Delaware Basins, warranting a Permian-wide study of underperforming wells. The Texas Oil and Gas Institute has access to all well data on University Lands, upholding production optimization objectives by identifying underperforming wells and determining whether production from these wells can be improved either by refracturing or artificial lift optimization. This study develops a thorough workflow to identify 300 underperforming wells out of the roughly 1,800 total horizontal Wolfcamp, Third Bone Spring, and Lower Spraberry unconventional wells on University Lands. The team first constructed two sets of type curves were constructed for each assigned geologically similar area—P50 based on production and P10 based on recent completion intensities. We then developed and calibrated numerical models for various Wolfcamp benches and the Lower Spraberry formations to forecast what each well could produce at a given lateral length. We then compared each well's normalized cumulative production and EUR to these type curves over time to determine low performance. Then, we performed RTA and/or AL analyses to diagnose the underperforming reasons. We then narrowed down potential candidates to enhance production by selecting wells based on high quality reservoir, low completion intensity, and suitable wellbore quality (if known). We determined that these shortlisted wells are potential refracturing or AL optimization candidates that University Land operators could improve despite critical commodity prices. Different completion methods over time significantly contributed to varying performance on University Land wells. For instance, larger ratios of hybrid fluid or cross-linked fluids compared to the total fluid pumped for the fracturing jobs yielded poorer performing wells. Wells considered for artificial lift optimization have marginal, daily operational costs and minimal workover times as recommendations, ensuring feasible implementation and consistent production across University Lands. Our workflow is very flexible depending on the available data, man power and expertise. Completion, production, reservoir, and geologic data from operators are used to evaluate operators' performance on 2.1 million acres, four formations, and eight intervals. The evaluations gave a better understanding to TOGI staff engineers and geologists of best operational and field development practices, and revealed insights on the key reservoir characters, recoverable potentials, and corresponding optimal well completion design and AL strategy.
Todea, Felix (Shell Canada) | Stephenson, Ben (Shell Canada) | Tomlinson, Alexa (Shell Canada) | Pratt, Heidi (Shell Canada) | Williams, Will (Shell Canada) | Acosta, Luis (Shell Canada) | Eggenkamp, Irma (Shell Canada) | Speidel, Brad (Shell Canada)
Abstract A fundamental conundrum common to hydraulically stimulated resource plays is how to understand the relative contribution of the sub-surface versus the drilling and completion parameters to well performance. A systematic methodology has been applied on a study of ~800 dry-gas wells in the Montney siltstone of British Columbia, with a variety of completion intensities, to extract the primary drivers of this multi-variate problem. The goal is to know how to tailor the drilling and completion design across the acreage as the sub-surface changes, to provide the optimum economic outcome. A systematic workflow, ‘Hypothesis-Based Development’, provides a rigorous framework to guard against biases, by forcing normalization of completions, well-spacing and the primary geological variability; in this play, depositional facies controlling effective permeability. The key analytical step, ‘Outlier Analysis’, is a methodology to prove, or disprove, hypotheses for well-performance by looking for opposite signatures in the very best and very worst wells; the ‘outliers’. A data analysis tool was created to interactively screen hypotheses against all the wells, explore trends and search for data-driven correlations. Being interactive, asset teams can arrive at solutions together, fostering alignment quickly, allowing focus to shift on how to affect development decisions. A long-standing challenge in the Montney study area was why there were no strong correlations between Hydrocarbons Initially in Place (HCIIP) parameters, like porosity, and well performance. After validating key hypotheses for well-spacing and completion intensity, it was concluded these two factors have a dominant influence on outlier well productivity in the Montney. The sub-surface signature was detected by choosing a high-graded, subset of ‘stand-alone’ wells, with a normalization for the completions intensity. A bulk-volume gas term, normalized for clay content and depth was found to be a proxy for reservoir quality and has a robust correlation (R ~ 0.78) with a well performance metric, normalized for 1000T proppant. These results from Outlier Analysis have many applications. Using the term for reservoir quality as a proxy for effective permeability, decisions around stage length can be optimized accounting for frac to frac production interference. A map of potential deliverability allows for faster recognition of under-performing wells, which can be flagged as candidates for intervention. Data from nearby operators can also be quickly assessed for completion optimization learnings, saving capital on duplication.
Abstract Maximizing recoveries and understanding associated reserve uplifts through the optimal completion design are major themes across North American unconventional plays. Thus, recognizing where the Montney sits in context to other plays in Western Canada is an integral component in evaluating the competitive landscape for investors and operators. This analysis compares completion trends across North America to highlight the impact of different completion designs on well performance. Additionally, the effect of completion designs on parent-child communication is analyzed. An overview of the industry regarding proppant intensity (lbs/ft) and the lateral length is presented, followed by an in-depth statistical analysis on the Montney and Deep Basin plays in the Western Canadian Sedimentary Basin (WSCB). The parent-child well analysis highlights how operators in the Montney Formation can maximize resource recovery while mitigating well failure. The study finds proppant intensity is the driving force behind the rate of change in the industry. However, larger completions can increase associated risk with offsetting well failures as plays move further into development mode. Our results suggest operators can maximize resource recovery through increased completion intensities and minimize parent well failure by moving toward pad completions. Introduction The Montney Formation, a Triassic siltstone that contains multiple stacked zones, is one of the most actively drilled plays in Canada. With the upstream oil and gas industry becoming increasingly competitive, it is imperative to understand where the Montney sits among its peers. Analyzing trends across North America, proppant intensity levels increased in recent years in many of the key resource plays in the U.S. However, operators in Canada tend to be more conservative and have yet to adopt similar completion designs. This study analyzes completion trends across North America and focuses on parameters such as proppant intensity and lateral length. A statistical evaluation of completions in the Montney and Deep Basin plays shows the effect of each parameter on EURs, and the parent-child analysis on the Montney Formation examines the risk associated with frac'ing offsetting child wells.