Technical papers, referencing CMG software, presented at the 2016 SPE Annual Technical Conference & Exhibition, Dubai UAE

Delineating Overburden Anomalies through Dip-Constrained Tomography for Improved Reservoir Imaging in an Offshore Carbonate Field
Paper: SPE 181599

Overburden (shallow) anomalies such as channels, sink holes, or karst features pose challenges for seismic time imaging, resulting in an obscured image below the anomalies i.e. pull-ups or push-downs. These anomalies can propagate down to the reservoir masking the image and create structural uncertainties. These relatively small scale (< 1 – 2 km) overburden anomalies cannot be resolved with conventional depth imaging usually, based on migration velocity analysis and residual move out (RMO) minimization only.

This paper proposes the application of dip-constrained tomography, in combination with RMO tomography to help resolve these shallow anomalies. […] Dip-constrained tomography was able to obtain a high resolution velocity model in the overburden and provided a robust seismic image essentially free of pull-up and push-down effects in the reservoir. The structural uncertainty in the reservoir was subsequently reduced. Inverting the dip term together with RMO term can potentially correct image distortions e.g. pull-ups and push-downs and focus the image simultaneously. The refined subsurface image can help optimize the reservoir model with less structure uncertainty and can enhance the production profile by providing more flexibility in well design and planning. The methodology was applied on a pilot area which gave quite encouraging results and leads to extend the pre-stack depth imaging to a full-field application.

© Copyright 2016. Society of Petroleum Engineers
Presented at the SPE Annual Technical Conference & Exhibition, 26 – 28 September 2016, Dubai UAE

A Methodology to Integrate Multiple Simulation Models and 4D Seismic Data Considering their Uncertainties
Paper: SPE 181608

Traditionally, integration between 4D seismic (4DS) and simulation data has been performed considering the 4DS data deterministically. However, there are uncertainties in the response of seismic. The goal of the methodology presented in this work is to compare the changes of dynamic properties estimated from 4DS and simulation models considering the uncertainties inherent to both data. […] To validate the methodology we use a synthetic dataset, with moderate complexity and seven uncertainties mapped, such as fault transmissibility, porosity, facies, and permeability.

[…] This information can be very useful to guide data integration. As an example, we show that region (4) can be used to select the simulation models that reproduce Sw or p behavior from 4DS, since 4D seismic data is more precise than the simulation estimates in this region. Other useful information from the proposed methodology is that the reservoir zones identified as region (2) can be used as a constraint to reinterpret 4D seismic data, as simulation estimates are more precise.

The methodology is a new way to evaluate the information from 4D seismic and simulation data considering uncertainties. The identification of these four regions can be useful in the parametrization phase of the history matching procedure (a complex process), as an additional tool to understand the properties in this procedure. The methodology also indicates possible locations to use reservoir engineering constraints to improve seismic interpretation, in regions where estimates from simulation are more precise than 4D seismic data. Moreover, we can use the methodology to determine critical reservoir locations to be reevaluated, those presenting disagreement between the two data source.

© Copyright 2016. Society of Petroleum Engineers
Presented at the SPE Annual Technical Conference & Exhibition, 26 – 28 September 2016, Dubai UAE

Advanced Production Data Analysis in Oil Carbonate Reservoirs
Paper: SPE 184484

In recent years there has been an increasing interest in the use of Advanced Production Data Analysis (APDA) methods for dynamic reservoir description. These methods analyze available daily production data, reducing Well Testing operations cost and avoiding production loss, with accuracy comparable to Pressure Transient Analysis (PTA). Different models have been proposed for homogeneous, coalbed methane and shale gas reservoirs. Unfortunately, carbonate reservoirs production are still being analyzed with homogeneous models.

This work presents the analytical derivation of two Advanced Production Data Analysis methods (Dynamic Material Balance and Blasingame Type Curves) based on the dual porosity model, to analyze daily production of Oil Carbonate reservoirs. Pseudosteady-state and transient (slabs and spheres) interporosity flow between matrix and fractures were considered.

The development was based on long-time approximate solutions of diffusivity equation in dual porosity system, for constant flow rate in a closed system with no-flow boundary. They were compared to exact solution in Laplace Space using Gaver-Stehfest algorithm. Then applying the appropriate dimensionless definition, both APDA methods were derived, including the generation of type curves. The validation was made using synthetic data generated by a numerical simulator for constant and variable flow rate.

Results confirm the applicability of current APDA methods based on homogeneous reservoirs, for the cases of transient interporosity flow between matrix and fracture. Nevertheless, additional considerations must be taken into account in the case of pseudo steady-state interporosity flow.

© Copyright 2016. Society of Petroleum Engineers
Presented at the SPE Annual Technical Conference & Exhibition, 26 – 28 September 2016, Dubai UAE

Solving the Challenges of Short- and Long-Term Production Forecasting and Uncertainty using a Fully-Coupled Implicit Integrated Production Modelling System
Paper: SPE 181427

Integrated modelling is of paramount importance while determining optimum development plans for any asset, especially for high-stakes offshore plays. It can be used for generating reliable reserve estimates and short to long-term forecasts. However, performing such studies has been a difficult proposition for the petroleum industry.

A number of logistical and technical challenges are present for any integrated modelling project. The logistical challenges appear because of multiple engineers working on multiple tools for different parts of the modelling work. The lack of timely feedback between teams often leads to the forecasts being unreliable. Moreover, several different tools and models need to be maintained for various disciplines and for different stages of asset development – presenting training and staffing issues. […]

In this paper, an innovative solution to the above mentioned problems is discussed. For demonstration purposes, a synthetic asset model has been developed, which represents a complicated deepwater asset. The asset has two heterogeneous reservoirs, with unique and complex fluids, such that modelling should account for fluid blending in the shared production network. A multi-user, multi-discipline, multi-fidelity tool is used that allows for collaboration and sharing of data between reservoir, production, and geomechanics engineers through a relational database. Multiple fidelities are used in the reservoir, wells, production network and geomechanics, with lower fidelity proxies typically being automatically generated from the more rigorous corresponding model – allowing for an easy-to-use, consistent and fit-for-purpose integration of model components. Even so, the adequacy of lower fidelity models is ensured by quick and easy comparisons with high fidelity models. All the relevant physics are modelled for a gas re-injection project, system bottlenecks are identified, and reliable short, medium and long-term forecasts are created using a consistent modelling approach. Forecasts are optimized for production, and valuation of forecast options including the timing and design of in-field drilling and compression upgrades are considered within the stochastic uncertainty of the dynamic reservoir models.

© Copyright 2016. Society of Petroleum Engineers
Presented at the SPE Annual Technical Conference & Exhibition, 26 – 28 September 2016, Dubai UAE