Integrated asset modeling covers the spectrum of reservoir development and ongoing operations activities. It can focus on optimization of daily production in a single well or be as expansive as making strategic portfolio management decisions. The wealth of data acquired or generated throughout a field’s lifecycle and use of multiple software tools facilitate a detailed understanding of hydrocarbon assets, careful monitoring of operations, and better overall modeling and management of resources.
Data and discipline-specific software packages enable individual asset team members to focus on their specific area of responsibility—planning, development, operations—creating specific models that estimate ultimate recovery, characterize reservoir conditions, or simulate various outcomes to evaluate risk. Their analyses and insights can then be collaboratively shared to further optimize return on investment.
Engineers responsible for each of the areas are finding that integrated asset modeling facilitates a holistic reservoir management approach that leads to a better understanding of resources and better-informed decisions. In this blog, we focus on production activities to illustrate the capabilities and benefits.
Limitations of Discipline-Specific Asset Models
Traditional asset modeling is characterized by individual members of the reservoir teams focusing on the data relevant to their area of responsibility—geology, petrophysics, simulation, well design, drilling, completion, production. However, discipline-specific software applied to a particular data type fails to account for data interdependencies that characterize the evolving nature of reservoirs.
With respect to understanding reservoir characteristics and planning for optimized production, each of these data describes only a portion or single aspect of a reservoir:
- geologic models depict subsurface structures, lithography, faults, and potential pay zones
- well logs provide additional information regarding porosity, permeability, and horizons
- simulation models help estimate ultimate recovery and predict reservoir performance
- wellbore locations and completion strategies focus on minimizing costs and risk while optimizing recovery
Initial EUR models are useful for planning surface infrastructure to capture, store, and transfer oil or gas, or tie-in with existing infrastructure. Then once the wellbore has been drilled and the well is operating, additional production data are used to refine reservoir models. Further into the life of the reservoir, additional seismic surveys, downhole pressure, and tracers can be used to update models to understand how subsurface changes are influencing production.
Integrated asset modeling depends on shared access to all relevant data to allow members of the asset team to evaluate and model their data in the context of other data to better understand the data interdependencies that influence production.
Integrated Asset Modeling Requires Shared Access to Data
One of the well-established software tools that facilitates integrated asset modeling is CoViz 4D which excels in its ability to easily integrate, visualize, and analyze a wide range of data types associated with all phases of a reservoir’s lifecycle. With respect to the production phase, CoViz 4D enables individuals in a multidisciplinary team to share the data specific to their area of expertise, integrating it with other relevant data, and visualize it as a static model of reservoir conditions or animate temporal data to show reservoir development over time.
A wide range of algorithms and geostatistic formulas, as well as workflows can be applied to the data to provide a better understanding of interdependencies among subsurface data with the goal of optimizing production. Three specific ways that CoViz 4D facilitates integrated asset modeling to provide a more detailed understanding of conditions that influence production include:
1. Greater Accuracy in Simulation Models
Accurate reservoir simulation models drive production planning. Through an iterative seismic history matching process reservoir engineers can cross-correlate seismic reservoir models with time-sequenced seismic data. CoViz 4D supports quantitative and qualitative comparisons of synthetic volumes with field-measured seismic data.
Guided by workflows to efficiently analyze and visualize the data, asset teams compare models, identify best matches, and update simulation models to more accurately reflect reservoir conditions. By correlating historical production data with simulations, reservoir engineers can predict production and locate good candidates for infill drilling.
2. Integrated View of Subsurface Data Identifies Conditions Affecting Production
Visualization of fluid production (near real-time, as well as cumulative), injection volumes, pressure data, and decline curves in the context of geologic and property models, can quickly identify sources of unexpected changes that affect production such as:
- geomechanical changes in structure that impede fluid flow or petrophysical properties that improve flow to pay zones
- fines (sand, silt, clay) migration in the completion zones affecting production flows
- incursion of nearby wells confirmed by tracers
- gradual or sudden production declines that indicate mechanical problems associated with production assets, e.g., casing, valves, pumps
Accurately identifying the factors that affect production is faster when all relevant data are integrated and visualized in an environment where geophysicists, and reservoir, drilling, and production engineers can collaborative apply their skills and experience to diagnose and remedy problems.
3. Visualize Production Over Time to Identify Opportunities
Through time-series visualization and analysis reservoir teams can learn how past production decisions have affected reservoir performance and impacted surface operations. Regular analysis of well events, logs, fluid production, injection and pressure data, and decline curves reveal fluid movement and saturation changes within a reservoir. Regular analysis of reservoir conditions can also reveal strain, stress, displacement, and seismic overburden shifts that potentially impact reservoir performance and production. Analysis of integrated datasets that depict evolving reservoir conditions in detail provides critical insight regarding historical and current production status to help identify opportunities for production improvements.
Engineers responsible for each of the areas are finding that integrated asset modeling facilitates a holistic reservoir management approach that leads to a better understanding of resources and better-informed decisions.
Integrated Asset Modeling Facilitates Better Decisions
The integrated asset modeling approach eliminates compartmentalized analysis of hydrocarbon resources. Software products such as CoViz 4D that facilitate sharing of data among individual disciplines enable significantly more efficient decision making, based on a more detailed understanding of evolving reservoir conditions. The ability to:
- easily integrate a wide range of geophysical, petrophysical, wellbore, and production data,
- apply algorithms and geostatistic formulas to better understand interrelationships among data, then
- quantitatively visualize and explore the integrated data over time
facilitates an integrated asset modeling approach that promotes better interdisciplinary communication and decision-making to optimize production throughout all phases of a reservoir’s producing life.