About Company

Flowgrids Limited was founded in 2011. Our focus is on petroleum engineering, geosciences, and training consultancy to create value for the upstream oil and gas industry.

Follow Us On Social
 

Project Experience

Our experience is global with focus on supporting the local oil & gas industry

Our team of engineers and geoscientist has the world-wide experience, gained from solving reservoir management problems in various oil and gas provinces around the globe

We tap on our global experience to
find sound solutions
tailored to meet reservoir management challenges

Projects Experience

Our multi-disciplinary team approach

 

Flowgrids Limited has a field-tested, technical staff
with the requisite experience and technical know-how
to solve reservoir management problems.
We have had opportunities to work on many
integrated studies to support field development planning.

When a client requests for our services, we identify experienced industry professionals to complement our technical staff to form a multi-disciplinary team of geologists, geophysicists, petrophysicist, petroleum production, and reservoir engineers. As a team, we develop advanced, fit-for-purpose workflows and harness appropriate computing hardware and software to execute the project. We maintain a clear line of communication with our clients throughout the project. We believe in building long-term relationships with our clients. We are committed to the delivery of quality results without compromise.

Since our founding in 2011, Flowgrids has executed many projects. Here is a sample of successfully completed projects.

Complementary Field Development Study

Flowgrids was asked to evaluate different reservoir management scenarios in a mature field to maximize reservoir productivity and forecast reserves. Flowgrids completed a comprehensive reservoir analysis to develop a static model as input for dynamic simulation. The fluid flow model was history-matched and used to forecast well and field-wide performance considering different reservoir management schedules. Flowgrids’ recommendations to the project sponsor included the optimum number and type of infill wells to drill, well placement and reservoir development schedule, and workover/intervention operations to maximize production from existing and infill wells.

Identification of early water breakthrough in horizontal well

Flowgrids was asked to identify the causes of early water breakthrough in a newly drilled horizontal well. An integrated reservoir engineering and dynamic modeling study was designed to diagnose cause of early water breakthrough in the horizontal well. After reservoir analysis, we recommended reservoir management solution of well recompletion to mitigate water production and to maximize well performance.

Integrated reservoir development studies: from Seismic interpretation to flow simulation, uncertainty analysis and exploration for nearby targets

Flowgrids has conducted many integrated field development studies. These are multi-disciplinary studies designed to give upstream oil and gas companies a blueprint for making reservoir management decisions. Typically, our geoscientists interpret seismic data, combine seismic data with petrophysical data to define the reservoir structure and faulting; capture the geology, incorporate the stratigraphy and structural models, and integrate the petrophysical properties, production and reservoir data to create the geomodel. Working in concert with the geoscientists, the reservoir and production engineers transform the static geomodel into a dynamic model. Upon calibration of the dynamic model to observed historical data, it is used with appropriate subsurface and surface facility constraints to forecast reserves, evaluate multiple field development scenarios, quantify uncertainty and risks of asset development. We also evaluate nearby exploratory prospects before recommending a field development plan to maximize the value of the asset.

Material Balance Study for STOOIP Validation and Reserves Estimation

The scope of the study included identification of dynamic units; evaluation of reservoir performance; estimation of in-place volumes and aquifer parameters; evaluation of possible increase in reserves and recovery factors.

Flowgrids used a four-step methodology to solve the problem:

  • Design multi-tank material balance models for layered reservoir using industry-standard software
  • Connect tanks via transmissibility multipliers to simulate inter- and intra-reservoir communication and identify dynamic units
  • Perform history match of pressure depletion to estimate aquifer properties, drive mechanisms and validate STOOIP obtained from volumetric methods
  • Use well and field constraint and the history-matched material balance models to forecast reserves and estimate recovery factors.

Value to the client: Aquifer properties, STOOIP, reserves forecast, and pressure depletion trends firmed decision of the client on the sequence of asset development and prioritization to save costs and maximize value.

Pressure transient test data analysis to support reservoir characterization

The scope of the study is the interpretation of multi-year pressure fall-off test data to support reservoir characterization.

Flowgrids used  industry-standard software to interpret multi-year falloffs using analytical and numerical models to determine

  • Permeability and its evolution with time
  • Change of skin effect with time
  • Sand continuity and reservoir boundaries
  • Well Injectivity characteristics

Value to the client:

  • Improved understanding of sand continuity and its impact on reservoir characterization (e.g., basis to constrain variogram parameters)
  • Well test derived reservoir properties (permeability and skin) to serve as input into the static and dynamic model(s)

Reservoir static model zonation and property correction

Flowgrids was asked to correct the misplaced zones introduced in a static model. We developed a  fit-for-purpose reservoir characterization workflow to identify the static model’s correct sequence of reservoir flow units and propagated the model with the corrected petrophysical properties. The revised model was used as  input for dynamic modeling. Relevant static model uncertainties were generated to support the client in making informed reservoir management decisions.