**Peer Reviewed**

**Source**

**SPE Disciplines**

**Journal**

**Conference**

**Theme**

**Author**

**Concept Tag**

- adjoint (1)
- arbitrarily (1)
- AWWE (1)
- Baumstein (1)
- BILU (1)
- boundary (1)
- boundary condition (1)
- breakthrough (1)
- change (1)
- chemical treatment (1)
- column (1)
- component (1)
- concentration (1)
- conservation (1)
- construction (2)
- convergence (1)
- core (1)
- data (1)
- deep learning (1)
- demulsification (1)
- demulsifier (1)
- Effectiveness (1)
- emulsion (1)
- Environmentally (1)
- equation (4)
- error (1)
- field (1)
- Figure (3)
- flow in porous media (3)
- Fluid Dynamics (3)
- formation damage (1)
- formation evaluation (3)
- formulation (3)
- function (1)
- gradient (1)
- Guddati (1)
- interfacial tension (1)
- inversion (1)
- iteration (2)
- knowledge management (1)
- layer (1)
- machine learning (1)
- method (2)
- migration (1)
- minute (1)
- model (1)
- multiphase flow (1)
- Multiscale (2)
- Multiscale Method (1)
- nanofluid (1)
- nanofluid formulation (1)
- neural network (1)
- objective (1)
- oilfield chemistry (1)
- operator (2)
- optimization problem (1)
- perfectly (1)
- performance (1)
- permeability (2)
- PML (1)
- preconditioner (1)
- pressure (3)
- problem (1)
- produced water (1)
- production (1)
- production control (1)
- production monitoring (1)
- prolongation operator (1)
- proppant (1)
- recovery (1)
- reference (1)
- reflection (1)
- region (1)
- reservoir simulation (3)
- restriction (1)
- restriction operator (1)
- result (1)
- rock/fluid interaction (1)
- sand (1)
- saturation (2)
- saturation equation (1)
- scalar (1)
- scalar AWWE (1)
- scaling method (2)
- scheme (1)
- score (1)
- shale gas (1)
- simulator development (2)
- solution (3)
- source (1)
- SPE (2)
- study (1)
- surfactant (1)
- TAM (1)
- temperature (1)
- time (1)
- time domain (1)
- transport (1)
- velocity (2)
- Wave Equation (2)

**Industry**

**Oilfield Places**

**Technology**

**File Type**

Conversional formulation of the gradient based on the cross-correlation of the derivatives of forward and backward particle displacement wavefield is derived from the second-order wave equations. During the process of back-propagation of the data residuals, the adjoint wave equations are just the same as the forward ones. Without preprocessing the data residuals before back-propagation, one cannot obtain a properly scaled gradient when applying the first-order velocity-stress differential equations. In this paper, based on the first-order elastic system in time domain, we propose a new form of adjoint wave equations, meanwhile corresponding formulation of gradient is described as well. Without integrating particle velocity in time to convert it to displacement and preprocessing the data residuals before back-propagation, the new scheme is tested to be more efficient. In addition by using dimensional analysis, it is obvious that the new formula of gradient is perfectly correct.

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

Arbitrarily wide-angle wave equations (AWWEs) are capable of imaging steep dips in heterogeneous media and convenient in numerical calculations, which enable them to be powerful tools for migration. The seismic wave modeling and migration are always carried out in a limited space, so an effective absorbing boundary condition (ABC) is required to avoid spurious edge reflections. In spite of an extensive utilization of perfectly matched layer (PML) in full wave equation, applications of PML for one-way wave equation (OWWE) are rare. In this abstract we derive a PML formulation for 3D scalar AWWEs to provide a good approach to suppress the undesired edge reflections. We finally formulate the PML in terms of a split field in the time domain and give out the discrete scheme using finite-difference method. Several numerical examples are given to show the effectiveness of the derived PML condition.

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (0.92)

An efficient two-stage algebraic multiscale solver (TAMS) that converges to the fine-scale solution is described. The first (global) stage is a multiscale solution obtained algebraically for the given fine-scale problem. In the second stage, a local preconditioner, such as the Block ILU (BILU) or the Additive Schwarz (AS) method, is used. Spectral analysis shows that the multiscale solution step captures the low-frequency parts of the error spectrum quite well, while the local preconditioner represents the high-frequency components accurately. Combining the two stages in an iterative scheme results in efficient treatment of all the error components associated with the fine-scale problem. TAMS is shown to converge to the reference fine-scale solution. Moreover, the eigenvalues of the TAMS iteration matrix show significant clustering, which is favorable for Krylov-based methods. Accurate solution of the nonlinear saturation equations (i.e., transport problem) requires having locally conservative velocity fields. TAMS guarantees local mass conservation by concluding the iterations with a multiscale finite-volume step. We demonstrate the performance of TAMS using several test cases with strong permeability heterogeneity and large-grid aspect ratios. Different choices in the TAMS algorithm are investigated, including the Galerkin and finite-volume restriction operators, as well as the BILU and AS preconditioners for the second stage. TAMS for the elliptic flow problem is comparable to state-of-the-art algebraic multigrid methods, which are in wide use. Moreover, the computational time of TAMS grows nearly linearly with problem size.

BILU, conservation, construction, convergence, equation, error, flow in porous media, Fluid Dynamics, formation evaluation, iteration, Multiscale, operator, permeability, preconditioner, pressure, problem, reservoir simulation, restriction, restriction operator, saturation, scaling method, simulator development, solution, TAM, time

Oilfield Places:

- Europe > Norway > North Sea > Tarbert formation (0.99)
- Europe > Germany > North Sea > Tarbert formation (0.99)

Recent advances in multiscale methods have shown great promise in modeling multiphase flow in highly detailed heterogeneous domains. Existing multiscale methods, however, solve for the flow field (pressure and total velocity) only. Once the fine-scale flow field is reconstructed, the saturation equations are solved on the fine scale. With the efficiency in dealing with the flow equations greatly improved by multiscale formulations, solving the saturation equations on the fine scale becomes the relatively more expensive part. In this paper, we describe an adaptive multiscale finite-volume (MSFV) formulation for nonlinear transport (saturation) equations. A general algebraic multiscale formulation consistent with the operator-based framework proposed by Zhou and Tchelepi (*SPE Journal*, June 2008, pages 267-273) is presented. Thus, the flow and transport equations are solved in a unified multiscale framework. Two types of multiscale operators--namely, restriction and prolongation--are used to construct the multiscale saturation solution. The restriction operator is defined as the sum of the fine-scale transport equations in a coarse gridblock. Three adaptive prolongation operators are defined according to the local saturation history at a particular coarse block. The three operators have different computational complexities, and they are used adaptively in the course of a simulation run. When properly used, they yield excellent computational efficiency while preserving accuracy. This adaptive multiscale formulation has been tested using several challenging problems with strong heterogeneity, large buoyancy effects, and changes in the well operating conditions (e.g., switching injectors and producers during simulation). The results demonstrate that adaptive multiscale transport calculations are in excellent agreement with fine-scale reference solutions, but at a much lower computational cost.

change, construction, equation, field, flow in porous media, Fluid Dynamics, formation evaluation, function, iteration, multiphase flow, Multiscale, Multiscale Method, operator, pressure, production control, production monitoring, prolongation operator, region, reservoir simulation, saturation, saturation equation, scaling method, simulator development, solution, transport, velocity, waterflooding

A continuing challenge in hydraulic fracturing of tight gas formations is associated with remediation of formation damage caused by fluid invasion into the porous media. Numerous studies documenting the use of complex nanofluids and surfactants to remediate formation damage have been reported. Recent publications have demonstrated that complex nanofluid additives resulted in lower pressures to displace injected frac fluids over conventional surfactants, and led to greater enhancement of gas and water production. These findings were also confirmed by several recent statistical analyses that took into consideration differences in the properties of treated wells. Many field case studies and supplementary laboratory data have illustrated benefits of complex nanofluid treatment over conventional surfactants. While these publications describe the successes of complex nanofluid treatment, the influence that the formulation composition has on its performance has not been fully investigated. In the present study, we prepared complex nanofluids with different chemical compositions and examined their performance in fluid recovery tests using columns packed with sand, ceramic proppant, and shale, as well as their ability to enhance permeability of sandstone cores to gas. We have established that performance of complex nanofluids in these applications was dependent on the amount of microemulsifed solvent in the original formulations and that optimal performance across all applications was achieved with a complex nanofluid formulation with a near-balanced composition.

breakthrough, column, core, Effectiveness, Figure, flow in porous media, Fluid Dynamics, formation damage, formation evaluation, formulation, knowledge management, nanofluid, nanofluid formulation, permeability, pressure, produced water, production, proppant, recovery, reservoir simulation, result, sand, shale gas, SPE, study, treatment

Oilfield Places:

- North America > United States > Texas > Fort Worth Basin > Barnett Shale (0.99)
- North America > United States > Louisiana > Many Oil Field (0.99)
- North America > United States > Arkansas > Fayetteville Shale (0.99)

Formation damage caused by water-in-crude oil emulsions can have a big impact on oil production. Chemical treatment is often applied by injecting surfactants known as demulsifiers to break the water-in-crude oil emulsions. Common demulsifiers used in the oilfield industry often contain chemicals that are deemed environmentally unacceptable. With the increasingly stringent environmental and safety measures for oilfield chemicals, there is a significant drive to develop more

environmentally friendly formulations for oilfield applications that are as efficient as existing chemicals. In this work, more environmentally friendly demulsifiers have been developed by systematically upgrading existing components in a conventional demulsifier with more environmentally acceptable components. The environmental impact of existing and upgraded formulations was evaluated using industry developed product rating systems. Demulsification tests were then

carried out to assess the performance of the newly developed formulations on several problematic oils.

Industry:

- Materials > Chemicals > Commodity Chemicals > Petrochemicals (1.00)
- Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

- Well Drilling > Drilling Fluids and Materials > Drilling fluid selection and formulation (chemistry, properties) (1.00)
- Well Drilling > Drilling Fluids and Materials > Drilling fluid management & disposal (1.00)
- Production and Well Operations > Production Chemistry, Metallurgy and Biology > Downhole chemical treatments and fluid compatibility (1.00)