The block-Jacobi partitioner (commit e360c00b7) uses grid interfaces
that are only available in CpGrid and this blocks introducing other
grid managers such as ALUGrid. Since the partitioner was only added
for OpenCL, guard special purposes accesses with HAVE_OPENCL.
This is a temporary measure and we will venture to restore the
partitioner later, although possibly restricted to CpGrid only.
Mostly to reduce the number of nested scopes in doLoadBalance_() and
to make the data flow a little easier to track for human readers.
While here, also use down-casts to pointer instead of references.
Doing so replaces try/catch blocks with simpler if/else blocks.
Reimplement face transmissibility calculation/extraction loop in
terms of helper functions elements() and intersections().
This commit calculates the various BxIP* summary output values such
as BOIP (block-level oil-in-place) and BGIPL (block-level
gas-in-place in liquid phase). While here, also extract the
block-level dissolved gas-oil-ratio (BRS) and vaporised
oil-gas-ratio (BRV).
If no cell has a valid corner-point geometry, typically caused by
using GDFILE to read non-finite data such as all ZCORN = -1.0E+20,
then we must not attempt to generate a grid structure. If we do, we
will typically just fail somewhere deep down in the corner-point
processing code and generate a diagnostic message that's hard to
decipher.
With this commit we instead output a diagnostic message of the form
Failed to create valid EclipseState object.
Exception caught: No active cell in input grid has valid/finite cell geometry
Please check geometry keywords, especially if grid is imported through GDFILE
This may not be a lot better than the original diagnostic
Processing grid
flow: ${ROOT}/opm-grid/opm/grid/cpgpreprocess/preprocess.c:768: is_lefthanded: Assertion `! searching' failed.
Aborted (core dumped)
but does at least suggest that the grid data may be faulty.
This commit switches the debug file's records of "failed" bubble and
dew point pressure calculations from a non-unique list of linearised
Cartesian indices to a unique list of (1-based) (I,J,K) tuples.
This format is hopefully easier to read for humans.
Thanks to [at]blattms for suggesting the gatherv() helper function
which greatly simplifies the communication pattern.
Example from selected time steps in a real field case with Cartesian
dimensions 137-by-236-by-58:
- Original
Finding the dew point pressure failed for 2 cells [1467066, 1467066]
Finding the dew point pressure failed for 8 cells [1467063, 1467063, 1467066, 1467066, 1467066, 1467066, 1467066, 1467066]
- This commit
Finding the dew point pressure failed for 1 cell [(71,89,46)]
Finding the dew point pressure failed for 2 cells [(68,89,46), (71,89,46)]
This is a potentially expensive operation and so we should not run
it unless such values are actually needed for output purposes (e.g.,
inter-region flow summary vectors).
This commit ensures that compute inter-region flow rates on all
ranks and collect those on the I/O rank using CollectDataToIORank.
We add a trivial EclInterRegFlowMap data member to the communication
object. This data member only knows the pertinent FIP region array
names, but uses existing read/write support to collect contributions
from all ranks into this "global" object. We then pass this global
object on to the summary evaluation routine.
This commit adds a new grid traversal that computes fluxes-presently
surface level component fluxes-for all bulk connections on the
current MPI rank. We aggregate those fluxes, if applicable, into a
container for inter-region flows, but this support could be extended
to capturing the full 3D vector flow rates for restart output if
needed.
This commit introduces a new helper class
Opm::EclInterRegFlowMapSingleFIP
that wraps a vector of
Opm::EclInterRegFlowMapSingleFIP
along with the associate array names (e.g., "FIPNUM" and any
additional "FIP*" arrays). We implement the same operations as the
*SingleFIP type and simply loop over the internal accumulators to
affect the operations.
Add unit tests to exercise the new class, including simulating
multiple MPI ranks that are communicated to a single I/O rank for
summary output purposes.
This commit introduces a new helper class
Opm::EclInterRegFlowMapSingleFIP
that wraps an object of type
Opm::data::InterRegFlowMap
along with the MPI rank's notion of a FIP region array definition
(e.g., the local FIPNUM array). The new single-FIP flow map is
responsible for accumulating local contributions to the inter-region
flows defined by that FIP array. In the case of connections between
MPI ranks, the rank that owns the lowest region ID accumulates the
associate flow rates.
Add unit tests to exercise the new class, including simulating
multiple MPI ranks that are communicated to a single I/O rank for
summary output purposes.
This is needed to get consistent estimates for the summary vectors
* {F,G,W}OP{R,T}{F,S} -- Free/Vaporized Oil Production
* {F,G,W}GP{R,T}{F,S} -- Free/Dissolved Gas Production
in the case of distributed wells.
Thanks to [at]blattms for the suggested fix.
The Flow specific PORV_RC and TMULT_RC solution arrays were tagged
as ECLIPSE compatible. Mark them as Flow specific so they do not
cause restart problems in the ECLIPSE compatible case.
This commit extends the guide rate reporting to always extracting
and reporting pertinent production guide rates at the well level
(i.e., WxPGR) if at least one of the groups in the well's upline has
an entry in GCONPROD. This is for increased compatibility with
ECLIPSE.
This commit uses the new GroupTreeWalker helper class to ensure that
we always extract and report pertinent injection guide rates at the
well level (i.e., WxIGR) if at least one of the groups in the well's
upline has an entry for the corresponding phase in GCONINJE. This
is for increased compatibility with ECLIPSE.
Prior to this change we would report zero-valued WWIGR vectors on a
real field case which made analysing simulation results needlessly
difficult.
This commit extracts a helper class, GroupTreeWalker, from the
current implementation of 'calculateAllGroupGuiderates()'. This is
in preparation of adding a similar approach to extracting WxIGR for
all wells for which at least one group in the upline has an entry in
GCONINJE.
The user can add visitor operations for wells and groups, typically
with side effects, and then choose whether to run a pre-order walk
(visit groups before their children) or a post-order walk (visit
children-i.e., wells, before their parents).
This guarantees, under the assumption that the group tree does not
have cycles, that we do not accumulate group-level guide rate values
until all of its children are fully evaluated. We use an iterative
depth-first post-order tree traversal with an explicit stack instead
of a recursive implementation.
The previous implementation, which tried to do the same kind of
child-to-parent accumulation, might visit a parent group multiple
times which in turn might lead to losing updates. This is a more
formalised approach to the value accumulation than was originally
employed.
We used to tie reporting these quantities to whether or not a group
had any guide rates for production (GuideRate::has()), but this is
clearly insufficient for injection guide rates.
This commit adds an overload set named
loadRestartGuideRates
which, collectively, initialises the contained GuideRate object
using guide rate values from the restart file. This is necessary,
but not quite sufficient, to restart models in prediction mode with
group-level constraints.
Mostly for readability in preparation of initialising the guide rate
object with values from the restart file. The new stages, each with
its own 'loadRestart*Data()' member function are
- Connection
- Segment
- Well
- Group
While here, also switch to using std::any_of() in place of a raw
loop.
The output layer expects its input values to be strictly SI, but we
know that the GuideRate container's values are in output units.
Forgotten in PR #3467 (commit 517db198f8).
This commit moves the bodies of the various 'dynamicDispatch_<>()'
cases out to separate helper functions. Not only does this reduce
the number of nested conditionals, it also helps reasoning about
each case in isolation and aids future maintenance.
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