def test_compute_accumulation(self):
problem = OneDimReservoir(self.inputs)
np.testing.assert_allclose(problem.compute_accumulation(0), 100.0)
return
def test_compute_transmissibility(self):
problem = OneDimReservoir(self.inputs)
np.testing.assert_allclose(problem.compute_transmissibility(0, 0),
4000.0)
return
def test_implicit_solve(self):
implicit = OneDimReservoir(self.inputs)
implicit.solve()
np.testing.assert_allclose(implicit.get_solution(),
np.array([1582.9, 1184.8, 1051.5, 1015.9]),
atol=0.5)
return
def test_implicit_solve_one_step(self):
implicit = OneDimReservoir(self.inputs)
implicit.solve_one_step()
np.testing.assert_allclose(
implicit.get_solution(),
np.array([1295.1463, 1051.1036, 1008.8921, 1001.7998]),
atol=0.5)
return
def test_implicit_heterogeneous_permeability_solve_one_step(self):
self.inputs['reservoir']['permeability'] = [10., 100., 50., 20]
implicit = OneDimReservoir(self.inputs)
implicit.solve_one_step()
np.testing.assert_allclose(implicit.get_solution(),
np.array([1085.3, 1005.8, 1001.3, 1000.1]),
atol=0.5)
return
def test_implicit_heterogeneous_permeability_and_grid_size_solve(self):
self.inputs['reservoir']['permeability'] = [10., 100., 50., 20]
self.inputs['numerical']['delta x'] = [2000., 3000., 1500., 3500]
implicit = OneDimReservoir(self.inputs)
implicit.solve()
np.testing.assert_allclose(implicit.get_solution(),
np.array([1295.6, 1039.1, 1019.9, 1002.5]),
atol=0.5)
return
def test_explicit_solve_one_step(self):
self.inputs['numerical']['solver'] = 'explicit'
explicit = OneDimReservoir(self.inputs)
explicit.solve_one_step()
np.testing.assert_allclose(explicit.get_solution(),
np.array([1506., 1000., 1000., 1000.004]),
atol=0.5)
return
def test_mixed_method_solve_crank_nicolson(self):
self.inputs['numerical']['solver'] = {'mixed method': {'theta': 0.5}}
mixed = OneDimReservoir(self.inputs)
mixed.solve()
np.testing.assert_allclose(mixed.get_solution(),
np.array([1642.0, 1196.5, 1043.8, 1009.1]),
atol=0.5)
return
def test_explicit_solve(self):
self.inputs['numerical']['solver'] = 'explicit'
explicit = OneDimReservoir(self.inputs)
explicit.solve()
np.testing.assert_allclose(explicit.get_solution(),
np.array([1689.8, 1222.3, 1032.4, 1000.0]),
atol=0.5)
return
def test_mixed_method_solve_one_step_crank_nicolson(self):
self.inputs['numerical']['solver'] = {'mixed method': {'theta': 0.5}}
mixed = OneDimReservoir(self.inputs)
mixed.solve_one_step()
np.testing.assert_allclose(mixed.get_solution(),
np.array([1370.4, 1037.8, 1003.8, 1000.4]),
atol=0.5)
return
def test_mixed_method_solve_one_step_explicit(self):
self.inputs['numerical']['solver'] = {'mixed method': {'theta': 1.0}}
mixed_explicit = OneDimReservoir(self.inputs)
mixed_explicit.solve_one_step()
np.testing.assert_allclose(mixed_explicit.get_solution(),
np.array([1506., 1000., 1000., 1000.004]),
atol=0.5)
return
def test_mixed_method_solve_one_step_implicit(self):
self.inputs['numerical']['solver'] = {'mixed method': {'theta': 0.0}}
mixed_implicit = OneDimReservoir(self.inputs)
mixed_implicit.solve_one_step()
np.testing.assert_allclose(
mixed_implicit.get_solution(),
np.array([1295.1463, 1051.1036, 1008.8921, 1001.7998]),
atol=0.5)
return
def test_is_transmissiblity_matrix_sparse(self):
problem = OneDimReservoir(self.inputs)
assert scipy.sparse.issparse(problem.T)
return
def test_implicit_solve_reverse_boundary_conditions(self):
self.inputs['boundary conditions'] = {
'right': {
'type': 'prescribed pressure',
'value': 2000 #psi
},
'left': {
'type': 'prescribed flux',
'value': 0 #ft^3/day
}
}
implicit = OneDimReservoir(self.inputs)
implicit.solve()
np.testing.assert_allclose(implicit.get_solution(),
np.array([1015.9, 1051.5, 1184.8, 1582.9]),
atol=0.5)
return