Carbon intensity (CI) of oil and gas production varies widely across global oil plays. Life cycle extraction from certain unconventional plays (
We perform well-to-refinery calculations of CI for major unconventional oil plays in North America and conventional plays in Asia Pacific. This approach accounts for emissions from exploration, drilling, production, processing, and transportation. The analysis tool is an open-source engineering-based model called Oil Production Greenhouse Gas Emissions Estimator (OPGEE). OPGEE makes estimates of emissions accounting using up to 50 parameters for each modeled field. This model was developed at Stanford University. Data sources include government sources, technical papers, satellite observations, and commercial databases.
Applied globally, OPGEE estimates show highest values in areas with extensive flaring of natural gas and very heavy crude oils - heavy oils require large energy inputs (
Unconventional production, especially from light tight oil is the most significant new source of fossil fuels in the last decade. Under a wide variety of carbon constraints, oil usage will continue for many decades and increase in the near term. Operators, governments, and regulators need to be able to avoid "locking in" development of suboptimal resources and instead provide incentives for shale operators to manage resources sustainably. This approach provides quantitative measures of such actions. Oil producers must prepare by eliminating development of marginal projects, elimination of flaring and venting, optimizing hydraulic fracture treatments, using improved recovery methods (
Drilling activities in the oil and gas industry have been reported over decades for thousands of wells on a daily basis, yet little effort was made to analyze this text in large-scale for information retrieval, sequence mining, and pattern analysis. Drilling reports contain interpretations written by drillers from noting measurements in downhole sensors and surface equipment, and can be used for operation optimization and accident mitigation. In this initial work, a methodology is proposed for automatic classification of sentences written in drilling reports into three relevant labels (EVENT, SYMPTOM, and ACTION) for hundreds of wells in an actual field. Some of the main challenges in the text corpus were overcome, which include the high frequency of technical symbols, mistyping/abbreviation of technical terms, and the presence of incomplete sentences in the drilling reports. This work describes state-of-the-art classification accuracy obtained within this technical language and illustrates advanced queries enabled by the tool.
This paper presents a new workflow for the simulation of in-situ combustion (ISC) dynamics. In the proposed method, data from kinetic cell experiments, depicting the combustion chemistry, are tabulated and graphed based on the isoconversional principle. The tables hold the reaction rates used to predict the production and consumption of chemical species during in-situ combustion.
This new method of representing kinetics without the Arrhenius method is applied on one synthetic and two real kinetic cell experiments. In each case, the new method reasonably captures the reaction pathways taken by the reacting species as the combustive process occurs. A data-density sensitivity study on the tabulated rates for the real case shows that only four experiments are required to capture adequately the kinetics of the combustion process. The results are, however, found to be sensitive to the size of the time step taken. The method predicts critical changes in the reaction rates as the experiment is exposed to different temperature conditions, thereby capturing the speed of the combustion front, temperature profile, and fluid compositions of a simulated combustion tube experiment.
The direct use of the data ensures flexibility of the reaction rates with time and temperature. In addition, the non-Arrhenius kinetics technique eliminates the need for a descriptive reaction scheme that is typically computationally demanding, and instead focuses on the overall changes in the carbon oxides, oil, water and heat occurring at any time. Significantly, less tuning of parameters is required to match laboratory experiments because laboratory observations are easier to enforce.
The emergence of hydrocarbons within shale as a major recoverable resource has sparked interest in fluid transport through these tight mudstones. Recent studies suggest the importance to recovery of microfracture networks that connect localized zones with large organic content to the inorganic matrix. The paper presents a joint modeling and experimental study to examine the onset, formation, and evolution of microfracture networks as shale matures. Both the stress field and fractures are simulated and imaged.
A novel laboratory-scale, phase-field fracture propagation model was developed to characterize the material failure mechanisms that play a significant role during the shale rock maturation process. The numerical model developed consists of coupled solid deformation, pore pressure, and fracture propagation. Benchmark tests were conducted to validate model accuracy. Laboratory-grade gelatins with varying Young’s modulus were used as scaled-rock analogs in two-dimensional Hele-Shaw cell setups. Yeast within the gelatin generates gas in a fashion analogous to hydrocarbon formation as shale matures. These setups allow study and visualization of host rock elastic-brittle fracture and fracture network propagation mechanisms. The experimental setup was fitted to utilize photoelasticity principles coupled with birefringence properties of gelatin to explore visually the stress field of the gelatin as the fracture network developed. Stress optics image analysis and Linear Elastic Fracture Mechanics (LEFM) principles for crack propagation were used to monitor fracture growth for each gelatin type.
Observed and simulated responses suggest gas diffusion within and deformation of the gelatin matrix as predominant mechanisms for energy dissipation depending on gelatin strength. LEFM, an experimental estimation of principal stress development with fracture growth, at different stages was determined for each gelatin rheology. Synergy between diffusion and deformation determines the resulting frequency and pattern of fractures. Results correlate with Young’s modulus. Experimental and computed stress fields reveal that fractures resulting from internal gas generation are similar to, but not identical to, type 1 opening mode.
The novelty of our work is that microfracture networks are imaged and modeled as they form rather than measured after the fact. Host rock elastic-brittle fracture and fracture network propagation mechanisms are triggered by internal gas generation, microfracture frequency, connectivity, and topology are linked to material properties in a direct fashion.
In the Midway Sunset Oil Field in Central California, operators inject steam into the shallow diatomite formation to enhance heavy oil recovery through imbibition, wettability alteration, and viscosity reduction, among other mechanisms. The injected steam, however, does not always remain in the reservoir or return through the wells. In two zones in the study area, the steam comes out at the surface, creating sinkholes, seeps, and steam outlets (see Figure 1b and 1c). These phenomena, called "surface expressions," pose safety and environmental hazards. This study examines attributes of the zones with surface expressions that may contribute to their occurrence. It is hypothesized that the surface expressions are caused by leakage of steam through old improperly abandoned wells, high injection pressure, structurally controlled flow patterns, high injection volumes, or flow along naturally occurring faults, among other possible factors. Spatial statistical analysis using logistic regression and classification trees is used to explore the relationship between the surface expressions and spatial attributes. The results point to a significant spatial correlation between the surface expressions and two predictors: concentration of plugged wells and geologic seal thickness. These predictors emphasize the importance of both properly abandoning retired wells and having sufficient seal between the producing zone and the surface.
The critical gas saturation in permeable sands was studied as a function of depletion rate and the presence of an aqueous phase as the major experimental variables. Voidage-replacement ratios (VRR = injected volume/produced volume) less than 1 were used to obtain pressure depletion with active water injection. Three different live crude oils were considered. Two of the oils are viscous Alaskan crudes with dead-oil viscosities of 87.7 and 600 cp, whereas the third is a light crude oil with a dead-oil viscosity of 9.1 cp. The critical gas saturation for all tests ranged from 4 to 16%. These values for critical gas saturation are consistent with the finding that the gas phase displayed characteristics similar to those of a foamy oil. For a given oil and depletion rate, the critical gas saturation was somewhat larger for VRR = 0 than it was for VRR = 0.7. The oil recovery correlates with the critical gas saturation (i.e., for a given VRR, tests exhibit greater oil recovery when the critical gas saturation is elevated). For the conditions tested, there was not a strong correlation of critical gas saturation over more than two orders of magnitude of the rate of pressure depletion, for a given VRR. Such behavior might be consistent with theoretical studies reported elsewhere that suggest that the critical gas saturation is independent of the pressure-depletion rate when the rate of depletion is small.
Compositional simulation is necessary for a wide variety of reservoir-simulation applications, and it is especially valuable for accurate modeling of near-miscible gas injection for enhanced oil recovery. Because the nonlinear behavior of gas injection is sensitive to the resolution of the simulation grid used, it is important to use a fine grid to accurately resolve the compositional and saturation gradients. Compositional simulation of highly detailed reservoir models entails the use of small timesteps and large, poorly conditioned linear systems. The high computational cost of solving such systems renders field-scale simulations practically unfeasible. The coupling of the flow and transport to the phase-equilibrium calculations adds to the challenge. This is especially the case for near-miscible gas injection, in which the phase state and the phase compositions are very strong functions of space and time.
We present a multiscale solver for compositional displacements with three-phase fluid flow. The thermodynamic phase behavior is described by general nonlinear cubic equations of state (EOS). The fully implicit (FI) natural-variables formulation is used as the basis to derive a sequential implicit (SI) solution strategy, whereby the pressure field is decoupled from the multicomponent transport. The SI scheme is mass conservative without the need to iterate between the pressure and transport equations during the timestep. This conservation property allows the errors caused by fixing the total-velocity field between the pressure- and transport-updating steps to be represented as a volume error. The method computes approximate pressure solutions—within a prescribed residual tolerance—that yield conservative fluxes on the computational grid of interest (fine, coarse, or intermediate). We use basis functions computed using restricted smoothing to allow for generally unstructured grids.
The new method is verified against existing research and commercial compositional simulators using a simple conceptual test case and also using more-complex cases represented on both unstructured and corner-point grids with strong heterogeneity, faults, and pinched-out and eroded cells.
The SI method and the implementation described here represent the first demonstrated multiscale method applicable to general compositional problems with complexity relevant for industrial-reservoir simulation.
Li, Qingyun (SLAC National Accelerator Laboratory and Stanford University) | Jew, Adam (SLAC National Accelerator Laboratory) | Kiss, Andrew (SLAC National Accelerator Laboratory) | Kohli, Arjun (SLAC National Accelerator Laboratory and Stanford University) | Alalli, Abdulgader A. (Stanford University) | Kovscek, Anthony (Stanford University) | Zoback, Mark (Stanford University) | Cercone, David (National Energy Technology Laboratory) | Maher, Kate (Stanford University) | Brown, Gordon (SLAC National Accelerator Laboratory and Stanford University) | Bargar, John (SLAC National Accelerator Laboratory)
Jew, Adam (SLAC National Accelerator Laboratory and Stanford University) | Li, Qingyun (Stanford University and SLAC National Accelerator Laboratory) | Cercone, David (National Energy Technology Laboratory) | Maher, Kate (Stanford University) | Brown, Gordon (Stanford University and SLAC National Accelerator Laboratory) | Bargar, John (SLAC National Accelerator Laboratory)
Alalli, Abdulgader A. (Stanford University) | Li, Qingyun (Stanford University and SLAC National Accelerator Laboratory) | Jew, Adam (SLAC National Accelerator Laboratory) | Kohli, Arjun (SLAC National Accelerator Laboratory) | Bargar, John (SLAC National Accelerator Laboratory) | Zoback, Mark (Stanford University) | Kovscek, Anthony (Stanford University)