|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
Cotrell, David (Baker Hughes, a GE company) | Hoeink, Tobias (Baker Hughes, a GE company) | Odusina, Elijah (Baker Hughes, a GE company) | Ghorpade, Sachin (Baker Hughes, a GE company) | Stolyarov, Sergey (Baker Hughes, a GE company)
Abstract In the current state of the oil and gas industry, unconventional resources are a significant source of the total production output. Unconventional wells remain profitable at various price points, because initial stimulation treatments can be tailored to changing market conditions, reflecting completion costs and (estimated) hydrocarbon prices. The same holds true for re-stimulation of already producing wells. Stimulation treatment "opens" up the subsurface to ultimately allow for better drainage of the reservoir hydrocarbons. The primary stimulation treatment currently in use is hydraulic fracturing, in which the wellbore is broken up into multiple stages, and highly pressurized fluid (oftentimes water) is pumped into each stage of the wellbore. This causes fractures to propagate away from the wellbore, which in turn enhances the local reservoir permeability and allows for economical production. Historically, the number of stages, and clusters per stage, for hydraulic stimulation has been based on wellbore horizontal length (e.g., 200 ft or 400 ft), or much valued previous experience in the same or similar area, as well as other investment considerations. Over time, a strong tendency has developed to place stages and clusters closer together to improve production. However, it is reasonable to assume that there will be a point beyond which adding another stage becomes more expensive than what is gained by increased production revenue from the greater stage count (i.e., less profitable depending on the time of investment). This scenario frames a classic optimization problem which is solved using Monte Carlo methods. Results show that optimal stimulation treatment configurations are robust for many objective functions related to the fracturing process (e.g., propped length and propped height). However, we find that objective functions related to production, production revenue, and profit often provide different optimum treatment configurations, and that those optima shift with respect to the considered timeframe. Because business decisions will ultimately be based on profit decisions over a given time span, we propose utilizing the appropriate objective function together with an integrated modeling approach such as presented here.
The business of unconventional resource extraction is inherently tied to short time scales, which are dictated by rapid decline curves in oil and gas bearing shale formations. In particular in the current operating framework of hydraulic fracturing, capital extensive decisions associated with well placement and construction, completion and treatment have to be made on a frequent basis to sustain ongoing cash flow obligations, oftentimes at low margin rates, and historically not always at profit. Non-optimal decisions, when compounded over many of those short investment cycles, can expose a business to significant risk of poor, even problematic, economic performance.
Unfortunately, making optimal decisions on unconventional reservoirs remains challenging. The combination of uncertainties in formation properties, numerous options for completion and treatment designs, and oil price volatility, frames a cross-disciplinary optimization problem with a large number of independent variables that existing tools are not equipped to solve.
This paper presents a methodology that goes beyond accepting the fate of inherent uncertainty, massive parameter space and market volatility; instead, it embraces uncertainty and leverages ambiguity to extract value for everyday decisions. At the core of this methodology is the concept of holistically modeling unconventional development. The approach integrates subsurface characterization, well placement and spacing, completion and treatment designs, production forecasts and economic considerations. We leverage scientific computing and modeling technology to cover relevant parameter space and utilize approximations and response surfaces to estimate metrics of statistical nature.
The application of uncertainty, sensitivity and optimization techniques allows us to move past isolated technical and economic decisions, e.g., from estimating propped fracture dimensions at a single stage to quantifying the probability of success for entire pad or field developments. Adopting this methodology furthermore leads to a shift in mind-set, in which assets are no longer considered as individual investments, but as constituents of a managed portfolio. This methodology enables businesses to transform their modus operandi by predicting the probability of persistent profit
Abstract Unconventional assets are crucial to the overall economic production of hydrocarbons. With the industry-wide trend of optimizing well spacing comes an increase in “frac hits”, i.e., adverse impacts on producing wells from stimulating a nearby well. Although in-zone frac hit events do not necessarily pose an environmental problem, data shows that existing, producing wells can be negatively impacted in a number of ways. Producing wells can be harmed when the pressure wave created during the hydraulic fracturing process is strong enough to cause pressure spikes or sand loading, either directly through fracture/fracture interactions or indirectly due to the propagating pressure wave reaching a nearby well drainage boundary with enough energy to cause damage. Consequently, finding ways to minimize the effect of fracture hits is currently a major focus in the oil and gas industry. In this paper, we consider an approach to mitigating frac hits that can be applied when initially performing acreage planning by ensuring sufficient well spacing during pad planning, or at stimulation time by limiting fracture lengths so that fractures do not directly interact with nearby producing wells. Introduction Drilling, completing and stimulating unconventional wells requires significant capital investment. Because unconventional assets are becoming increasingly more important, there is an industry-wide tendency to maximize acreage production by optimizing well spacing in unconventional reservoirs. However, reduced well spacing has led to “frac hits”, here defined as unwanted interactions between a hydraulically stimulated well and a nearby producing well. Given the amount of in-fill drilling currently afoot in the industry (Vidma et al. 2019), and the number of future horizontal wells forecasted to be fractured (Cook et al. 2016; Perrin, et al. 2016; Cook et al. 2018), the issue of frac hits has become of significant concern. Field data demonstrates that producing wells can be negatively impacted in several ways. For example, the pressure wave created during the hydraulic fracturing process can interact with the existing well drainage boundary either directly or indirectly. Direct interactions include fracture/fracture interactions such as strong pressure spikes or fracture clogging, and may include interactions via fracture networks as well. Indirect interactions may occur when the hydraulic stimulation-induced pressure wave propagates through the porous subsurface and reaches a nearby well with enough energy to cause damage. Damages can occur to downhole artificial lift equipment, through sand loading or pressure spikes, or manifest as production re-routing from one well to another or as production re-distribution within a well.
The success of an unconventional hydrocarbon development depends on effective stimulation of reservoir rocks maintaining well integrity during stimulation and production especially for the Vaca Muerta. While key decisions such as well spacing and completion intensity greatly impact the economics of the asset development, well integrity remains as the key risk that must be mitigated to warrant effective stimulation of the formation. In cooperation with SHELL [Bai 2016, Yeh 2018] we have developed a coupled geomechanical and reservoir modeling workflow that can address the interplay of well spacing and completion intensity, while mitigating the risk of casing deformation.
Integrated geomechanical and reservoir modeling incorporates a range of multi-disciplinary inputs such as the layered geologic model, well drilling and landing zone, completion design, operational management strategies, and production performance. In a first step the hydraulic fracturing model is calibrated to best available field data. After sufficient calibration quality is reached the forecast quality at neighboring wells is verified. Then the model is used in the forecast mode to optimize well spacing for single or multi-layered field development, including optimal well landing zone identification and completion design that attempts to maximize Net Profite Value (NPV) and Estimated Ultimate Recovery (EUR), while also predicting the potential magnitude and location of bedding plane shear induced casing deformation events.
The results provide critical inputs for decisions on well spacing, well landing and completion designs with reduced number of field trials for achieving optimal operational conditions. In addition, the workflow provides valuable insights for critical data acquisition to evaluate and forecast field performance.
To address the industry-wide challenge to increase predictability and confidence in numerical models an appropriate characterization of rock heterogeneity and handling of uncertainties of subsurface parameters is crucial. These two critical functionalities are addressed with the developed technology. Firstly, we capture the subsurface layering heterogeneity, i.e. thickness and spatial frequency of shale, carbonate and ash layer occurrence, along with natural fractures or planes of weakness with a truly 3D anisotropic modeling approach. Secondly, we balance the estimation of uncertainty ranges in model input parameters with the ability to converge to a calibrated geomechanical model with sufficient forecast quality for the evolution of the fracture network and resulting hydrocarbon production. After the successful calibration,this technology has shown to be appropriate for the accuracy of prediction of well EUR outside the calibrated conditions and is today standard approach for hydraulic fracture modeling in SHELL [Bai 2016].
A case study with TOTAL [Pourpak 2019] is presented in this paper to demonstrate the effective way of incorporating subsurface heterogeneity and variability into hydraulic fracture models to achieve a calibrated reservoir model and to use that model in the forecast mode to predict EUR along with all costs and NPV for a large window of variability of operational parameter.
In addition, the risk of shear deformation along bedding planes, which is believed to be one of the main mechanisms for casing deformations and well integrity issues, is investigated and measured These quantifications of casing deformation risk are used today as constraint in the optimization process to achieve profitable production and minimization of casing deformation at the same time.
Abstract A paradigm shift in dealing with subsurface uncertainty in hydraulic fracturing treatments is introduced. The mathematically rigorous application of uncertainty and sensitivity analyses for a proposed stimulation of a lateral well within an unconventional reservoir in the Marcellus with limited formation data delivers the ability to identify the optimum treatment parameters and to quantify its probability of success. Selection of the optimum reservoir stimulation treatment is achieved by systematically investigating thousands of hydraulic fracture simulations over a large parameter space covering formation properties with inherent uncertainties (e.g., stress gradients, leak-off coefficients) and tunable treatment parameters (e.g. pumping rates, fluid and proppant properties, perforation spacing), and computing an objective function. Operators commonly select objectives based on technical (e.g., propped fracture length, fracture height containment), operational and investment considerations. Here, the average fracture conductivity at closure is selected as the primary technical objective to be maximized. A subsequent uncertainty analysis of the optimum treatment plan that expressly includes the limits of formation property knowledge quantifies the probability of success. Production forecasts of specific cases illustrate the range of possible outcomes. Results from more than 12,000 hydraulic stimulation simulations demonstrate a wide distribution of results in terms of average fracture conductivity. Surprisingly, only a small, isolated fraction (< 5%) of the design space returns clearly superior results compared to the majority of investigated scenarios. The optimum treatment designs in this study are associated with relatively low volumes of a gel treatment pumped at relatively high rates. Production simulations illustrate that the best 10% of cases significantly outperform production over the first two years by approximately 50%. Collectively, the approach presented here illustrates the application of uncertainty and sensitivity analyses on several thousand simulations that cover a large, realistic parameter space. Embracing uncertainty, this approach enables identification of the best treatment plan and quantification of the probability of success given limited formation data. In addition, this methodology offers input for risk assessment and return on investment decisions.